Abstract
Tumor mutational burden (TMB) has emerged as a potential surrogate for neoantigen load and an indicator of immune checkpoint (IC)-blockade response; however, its precise significance in breast cancer (BC) is not fully understood. Here, we comprehensively characterized the genomic repertoire of BCs with a TMB ≥ 10 mut/Mb (TMB-high [n = 527]) to identify putative predictors of importance. The predominant mutational signature was apolipoprotein B mRNA-editing enzyme catalytic polypeptide (APOBEC) in 64.7% of tumors. TMB-high BCs were enriched in KMT2C, ARID1A, PTEN, NF1, and RB1 alterations, which are associated with APOBEC mutagenesis. Further identified were loss-of-function ARID1A and PTEN alterations, which are linked to immune cell exclusion. ESR1 p.E380Q prevailed among all ESR1 hotspot mutations, supporting APOBEC-mediated effects. Finally, mutations in DNA damage response and repair genes were seen at a higher frequency than in non-TMB-high BCs. These findings provide justification for exploring combined pharmacologic inhibition to improve IC-based efficacy.
Similar content being viewed by others
Introduction
Tumor mutational burden (TMB) is a quantifiable numeric indicator of the total number of acquired somatic mutations in a delineated region of the genome (i.e., mutations per megabase [mut/Mb]). Consequently, TMB has emerged as a surrogate biomarker for the predicted neoantigen formation, to identify patients that may benefit from immune checkpoint (IC)-blockade. The latter concept is analogous to microsatellite instability (MSI)-high tumors that are attributed to mismatch repair impairment with ensuing somatic hypermutation1. Following the authorization of pembrolizumab by the Food and Drug Administration (FDA) on June 16, 2020, in the setting of unresectable or metastatic TMB-high solid tumors2, defined as ≥ 10 mut/Mb, TMB determination has emerged as a metric of paramount importance for therapeutic decision making.
Breast cancer (BC) has long been considered an immunologically “cold” tumor, with triple negative breast cancer (TNBC) exhibiting the greatest immune cell enrichment among different subtypes, as demonstrated by tumor-infiltrating lymphocytes (TILs) and gene expression signatures3,4. Nonetheless, only a subset of patients achieves therapeutic benefit from IC-blockade. At present, a practical ascertainment of tumor immune cell activation involves the determination of stromal and intra-tumoral TILs by histopathologic evaluation and application of programmed death-ligand 1 (PD-L1) protein expression by immunohistochemistry. Intuitively, high TMB serves as a marker for eliciting a T-cell immune response due to an increased neoantigen load, yet IC-blockade response does not necessarily always correlate with TMB. On that account, predictive markers of immune response are urgently needed to better tailor treatment decisions.
Studies have yet to show that a defined TMB threshold can recognize potential patients that may derive benefit from IC-blockade therapy across various tumor types5. TNBC is considered the most aggressive and immunogenic BC subtype, with most studies investigating the efficacy of IC-blockade in these tumors. The initial phase Ib clinical trial (KEYNOTE-012) assessed the efficacy of single-agent pembrolizumab in PD-L1+ metastatic TNBCs in patients who had predominantly undergone multiple lines of therapy with an overall response rate of 18.5%6. Subsequent studies (KEYNOTE-119) explored the effectiveness of single-agent pembrolizumab in the metastatic setting as a second- or third-line treatment option for TNBCs with no change in overall patient survival when compared to chemotherapy7. Thereafter, combination regimens with chemotherapy to “prime” the immune system as a result of chemotherapy-induced immunogenic cell death were explored8. Importantly, only a subset of PD-L1+ metastatic TNBCs appear to be responsive to IC-blockade, which supports the notion of combination therapies9. An additional essential parameter to consider is whether the tumoral neoantigen load induces an immune response. Tumors exhibiting a high neoantigen load that also show a positive correlation with CD8+ T-cell infiltration, such as metastatic endometrial cancer (KEYNOTE-158) and metastatic melanoma10, have been reported to confer greater response rates with IC-blockade treatment modalities5. Conversely, those who lack the latter correlation (e.g., breast and prostate cancer) have shown not to portend a response rate greater than 20%5.
In this study, we queried a large dataset of clinically sequenced BCs to characterize the genomic landscape of BCs with a TMB ≥ 10 mut/Mb (i.e., TMB-high BCs), seeking to identify genetic alterations that may impact clinical response to IC-blockade. We report that patients with TMB-high BCs exhibit enrichment in somatic alterations beyond PIK3CA and TP53 that include KMT2C, ARID1A, PTEN, NF1, and RB1, which have been linked to apolipoprotein B mRNA editing enzyme catalytic polypeptide (APOBEC)-induced mutagenesis and immune cell exclusion from tumor samples. Moreover, DNA damage response and repair (DDR) genes were altered at a higher frequency in TMB-high BCs, suggesting that alternate therapeutic avenues could potentially be exploited. Our study demonstrates that TMB-high BCs harbor a composition of alterations that can be explored beyond IC-blockade and presents insight with promising avenues for improved patient outcomes.
Results
Patient characteristics
To examine the proportion of BCs with a TMB ≥ 10 mut/Mb we leveraged the Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT) platform and identified a total of 527 tumors (primary, n = 121 [23%]; metastatic, n = 406 [77%]) from 462 patients who met the inclusion criteria. The entire MSK-IMPACT BC cohort at the time of this analysis was comprised of 7894 tumors from 6589 patients who underwent targeted genomic profiling. The mean age at time of diagnosis was 54.2 years (range, 28–82) and the TMB spanned from 10.0 to 394.1 mut/Mb (mean: 18.4; median: 14.0). The mean TMB across the entire MSK-IMPACT BC clinical sequencing cohort was 4.6 mut/Mb (median: 3.5). Overall, invasive ductal carcinoma (IDC) was the most common histologic subtype seen in 62.6% of tumors, followed by invasive lobular carcinoma (ILC) at 26%. The baseline patient and clinicopathologic characteristics are collectively summarized in Table 1.
Distribution of genomic alterations in TMB-high BCs
We next sought to explore the genomic landscape of TMB-high BCs and found identifiable differences in the frequency of alterations when compared to the rest of the cohort (i.e., BCs with a TMB < 10 mut/Mb = non-TMB-high BCs). Tumors cataloged as having ≥ 10 mut/Mb comprised 6.7% of the entire MSK-IMPACT BC clinical sequencing cohort (Fig. 1a). Among TMB-high BCs, 75.1% of tumors had a TMB ranging from 10.0 to 19.9 mut/Mb, whereas 24.9% had a TMB ≥ 20 mut/Mb (Fig. 1b). TMB-high BCs showed a statistically significant enrichment in somatic alterations in genes including PIK3CA (60% vs. 33%; p = 1.61 × 10−37), TP53 (57% vs. 41%; p = 2.36 × 10−11), and CDH1 (34% vs. 13%; p = 6.48 × 10−43), when compared to the non-TMB-high BCs (Fig. 1c). No appreciable differences were seen when stratifying TMB thresholds by biomarker status in TMB-high BCs.
a Schematic representation of the percentage of TMB-high BCs in the MSK-IMPACT clinical sequencing cohort. Bar chart depicts the mean TMB among the two respective groups. b Bar chart showing the TMB distribution across the cohort with the corresponding proportion of tumors. c Oncoprint depicting the repertoire of gene alterations in the study cohort by the targeted MSK-IMPACT platform, sorted by decreasing frequency. The top 10 most frequently altered genes are presented, in addition to select genes of clinical importance. Tumors are shown in columns and genes in rows, with the percentage of alterations displayed on the right. d Distribution of common metastatic sites sequenced within the cohort with corresponding alteration frequency of select genes. Alteration legend is the same as in 1c. The icon of the human figure is created in https://BioRender.com. Abbreviations: Cerebrospinal fluid (CSF); Gynecologic tract (GYN tract). e Bar chart demonstrating the percentage of CD274 amplification in TMB-high and non-TMB-high BCs. f Circos plot summarizing the distribution of fusions in TMB-high BCs. Inter and intrachromosomal translocations are marked by the colored lines. The numeric digits signify the chromosome number of the corresponding event.
To investigate the distribution of specific genomic alterations in metastatic tumors, we explored curated sites of involvement and determined the alteration frequency of key genes. Among metastatic BC samples, the most frequent site sequenced was the liver (n = 89), followed by lymph node (n = 70) and bone (n = 65) (Fig. 1d). Alterations in ESR1 were found in 27% of liver metastases, whereas CDH1 mutations and ERBB2 amplifications were present in ≥ 50% of bone and brain metastases, respectively. This mutational preference for specific metastatic sites is in keeping with prior findings11,12. Amplification of CD274, the gene encoding for PD-L1, was not common and was seen in 0.9% and 0.6% of TMB-high and non-TMB-high BCs, respectively (Fig. 1e).
Lastly, we explored the structural variant distribution across all TMB-high BCs using MSK-IMPACT and in a subset of tumors reflexed to MSK-Fusion (n = 108), a targeted RNA-based assay, and identified 42 fusions involving various loci of the genome (Fig. 1f). Among these, the most recurrent in-frame fusions involved ESR1 (Chr. 6). Further identified were the androgen receptor (AR) splice variant-7 (AR-V7) (n = 13) and ESR1 out-of-frame fusions (n = 5) by MSK-Fusion. The latter events resulted in the deletion of the estrogen receptor (ER) alpha (ERα) ligand-binding domain.
TMB-high BCs exhibit a dominant APOBEC signature
Mutational signature analyses were conducted employing the signature multivariate analysis (SigMA) pipeline, a computational tool approach, which is tailored to generate mutational signatures from targeted sequencing panels13. Dominant mutational signatures were inferred in tumors with ≥ 8 curated exonic single-nucleotide variants or small indels. We detected a dominant APOBEC signature in 64.7% of TMB-high BCs, followed by a homologous recombination deficiency (HRD) signature in 23.1% (Fig. 2a). Among different BC subtypes, the greatest contribution of the HRD signature was seen in TMB-high TNBCs (Fig. 2b), whereas the highest TMB was seen in BCs with a dominant APOBEC signature (mean: 19.6 mut/Mb; median: 15.8 mut/Mb) (Fig. 2c). Using a non-parametric Wilcoxon Rank-Sum test (Mann–Whitney U test), TMB values were significantly higher in tumors with a dominant APOBEC signature when compared to HRD (p = 1.6 × 10−12), clock (p = 0.002), and ROS/5FU (p = 0.005). The predominant contribution of APOBEC-related mutations is consistent with previous findings implicating genes such as PIK3CA, KMT2C, ARID1A, NF1, and ESR1 in BC oncogenesis14,15,16,17.
a Bar chart demonstrating the distribution of inferred dominant signatures in TMB-high BCs (n = 515; signatures were not available for 12 tumors). b Pie charts summarizing mutational signatures according to receptor status. Unavailable signatures are incorporated in the other category. c Box plots depicting the range of TMB values among different signatures with ≥2 tumor samples. Asterisks denote differences of statistical significance: *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001). Horizontal line in box plots denotes median value. d Representative TMB-high BCs with a dominant MSI signature, showing loss of mismatch repair proteins at the protein level by immunohistochemistry, alongside corresponding H&E-stained photomicrographs. Each row represents one tumor. Rows 1 and 2: Loss of MLH1 and PMS2. Row 3: Loss of PMS2. Scale bars, 100 μm. e Box plot (left panel) depicting the range of TMB values in tumors with positive (SP142: ≥ 1%; SP263: CPS ≥ 10) and negative PD-L1 expression by immunohistochemistry (unpaired t-test). Mean value is demonstrated, and the quartile calculation is exclusive of the median. Representative PD-L1 positive and negative cases with corresponding H&E-stained photomicrographs (right panel). Scale bars, 100 μm.
Immunohistochemistry for mismatch repair proteins was available for select cases with an MSI signature and showed loss of protein expression (Fig. 2d). The mean TMB for TMB-high BCs with a dominant MSI signature was 19.5 mut/Mb (median: 15.3). PD-L1 expression by immunohistochemistry was available for a subset of TMB-high BCs (n = 38), with 9 tumors being positive (SP142, n = 8; SP263, n = 1) and 29 negative (SP142, n = 24; SP263, n = 5) (Fig. 2e). Collectively, these data underscore the frequency of APOBEC mutagenesis in TMB-high BCs with resultant genomic alterations, in addition to the contribution of tumors with MSI signatures that may benefit from IC-blockade therapy. Moreover, our results corroborate previous findings with a dominance of APOBEC-mediated mutagenesis in tumors with increased TMB18,19.
ESR1 p.E380Q is the predominant ESR1 hotspot mutation in TMB-high BCs
Mutations afflicting the ESR1 gene were identified in 13% of TMB-high BCs and, surprisingly, 35% of ESR1-mutated tumors harbored hotspot missense mutations involving codon 380 (i.e., ESR1 p.E380Q/K) (Fig. 3a). Overall, the latter variants were seen in 5.8% of non-TMB-high ESR1-mutated BCs. Further examining the ESR1 codon 380 mutations identified, we noted that 89.3% of these variants (n = 25/28) demonstrated an APOBEC signature in agreement with a previous report, in contrast to other ESR1 hotspot mutations, which were primarily non-APOBEC associated (Fig. 3b)15. Interestingly, a subset of TMB-high BCs harboring ESR1 p.E380Q mutations co-occurred with likely oncogenic FOXA1 mutations, including hotspot missense mutations, which are typically reported to be mutually exclusive (Fig. 3c)20. Co-occurring FOXA1 mutations were subclonal events compared to ESR1 mutations in all but one tumor. FOXA1 upregulation has been reported to activate HIF-2α transcription in ER+/human epidermal growth factor receptor 2 (HER2)− metastatic BCs, conferring endocrine resistance21. Consistent with previous findings, no MAP2K1 hotspot mutations were identified in this subset of tumors20. Given that both ESR1 and FOXA1 hotspot mutations are well-established mediators of resistance to anti-endocrine therapy, alternate therapeutic avenues need to be explored in TMB-high BCs with concurrent ESR1 and FOXA1 hotspot mutations.
a Schematic truncated representation of the ligand-binding domain of ERα demonstrating the prevalence of ESR1 p.E380Q/K hotspot mutations in TMB-high BCs (top panel) and non-TMB-high BCs (bottom panel). The mutation frequency is represented by the height of each lollipop (y-axis). Green circles: missense or in-frame mutations; Black circles: truncating or splice site mutations. Bar chart (right panel) showing the percentage of ESR1 p.E380Q/K mutations among all ESR1-mutated BCs in each respective cohort. b Pie chart and a bar of pie chart summarizing the prevalence of mutational signatures according to the mutated ESR1 hotspot codon. c Oncoprint depicting co-occurring FOXA1 alterations with ESR1 gain-of-function hotspot mutations. The annotated ESR1 hotspot mutations show the corresponding likely oncogenic FOXA1 mutations, including hotspot missense mutations (n = 4).
TMB-high BCs harbor an increased proportion of alterations in DDR genes
The efficacy of PARP inhibitors in the metastatic setting for germline BRCA1/2 mutation carriers, based on results from the OlympiAD22 and EMBRACA23 trials on improved progression-free survival (PFS), has drawn much intrigue in targeting BRCAness. In addition, inferred mutational signature analyses revealed 30% of our dataset to exhibit dominant HRD and MSI signatures that instigated further study. On these grounds, we assessed the distribution of DDR gene alterations across the entire BC cohort and found a higher occurrence of somatic alterations in TMB-high BCs (Fig. 4a). TMB-high BCs were enriched in gene alterations implicated in pathways such as homologous recombination (i.e., BRCA1, RAD50, and RAD51), checkpoint blockade (i.e., ATM, ATR, and CHEK1), and mismatch repair (i.e., MLH1, MSH2, MSH6, and PMS2). Of these genes, we observed likely oncogenic hotspot mutations in RAD51C (n = 6) (Fig. 4b) and POLE (n = 6) (Fig. 4c) in multiple tumors when compared to the non-TMB-high BCs at 1 and 3 tumors, respectively. Interestingly, all tumors with the POLE p.E18K hotspot mutation had a dominant APOBEC signature; admittedly, these mutations were not present in the exonuclease domain.
a Distribution of all (left panel) and driver (right panel) DDR gene alterations in TMB-high BCs (red) and non-TMB-high BCs (blue). Abbreviations: Mismatch repair (MMR); Nucleotide excision repair (NER); Homologous recombination (HR); Fanconi anemia (FA); Miscellaneous (Misc.). Schematic representation depicting the protein domain(s) with likely oncogenic hotspot mutations in b RAD51C and c POLE. The mutation frequency is represented by the height of each lollipop (y-axis). Green circles: missense or in-frame mutations; Black circles: truncating or splice site mutations; Arrows: hotspot mutations.
Metastatic TMB-high TNBCs are enriched in mutations related to PI3K/AKT signaling and potential immune cell exclusion
Given the modest treatment response in BCs subjected to IC-blockade, we surveyed primary and metastatic TMB-high TNBCs to assess for potential somatic mutations that may be associated with immune cell modulation. We ascertained an enrichment in truncating ARID1A, RB1, and MAP3K1 mutations in metastatic TMB-high TNBCs (Fig. 5a). AKT1 gene amplifications and AKT1 p.E17K hotspot mutations were present in 13% of metastatic TMB-high TNBCs but were not seen in primary TMB-high TNBCs in our series. One ESR1 p.G521V missense mutation of unknown significance was identified in a primary TMB-high TNBC in a patient previously treated with anti-endocrine therapy for contralateral breast cancer. Pathogenic TP53 alterations were present in 77% of metastatic TNBCs, which have been reported to promote immune evasion and abrogation of immune signaling24. Based on SigMA, dominant APOBEC and HRD mutational signatures were seen in 39.1% and 36.8% of TMB-high TNBCs, respectively. Eleven tumors (12.6%) had an MSI signature, of which one patient had documented Lynch syndrome. These findings imply that the phosphoinositide 3-kinase (PI3K)/AKT pathway and additional intrinsic genomic events may play crucial roles pertaining to treatment response that warrant investigation with functional studies.
a Oncoprints displaying select genetic alterations present in primary and metastatic TMB-high TNBCs. Primary and metastatic tumors from the same patient are annotated by the black and white circles. b Box plot (left panel) demonstrating the distribution of TILs in primary TMB-high TNBCs (n = 22) according to the International TILs Working Group recommendations. Mean value is demonstrated, and quartile calculation is inclusive of the median. Representative H&E-stained photomicrographs of primary TMB-high TNBCs (right panel) with a prominent lymphocytic infiltrate are shown. Scale bars, 100 μm. c Stacked box plots collectively showing copy number alterations assessed by FACETS in tumors with co-occurring loss-of-function (≥ 3) mutations in specific genes. Abbreviation: Whole genome duplication (WGD).
Next, primary TMB-high TNBCs were assessed for the percentage of TILs using recommendations by the International TILs Working Group (mean: 17.3%; median: 10%) (Fig. 5b)25. Past work has suggested that early-stage TNBCs with at least 30% TILs have prognostic implications conferring excellent survival26. Among tumors exhibiting ≥ 30% TILs, 4 of 5 tumors lacked mutations in ARID1A or PTEN, whereas one tumor had a PTEN p.T319* nonsense mutation with a dominant MSI signature. Importantly, loss-of-function alterations in these genes have been reported to associate with immune cell exclusion. In addition, 2 TMB-high TNBCs with increased TILs (30% and 60%) had RB1 splice site mutations. Co-occurring RB1 and TP53 alterations have been previously shown to display greater T-cell-inflamed signatures and CD8+ lymphocytes in bladder urothelial carcinoma27. Moreover, immunohistochemistry for AR was previously performed in a subset of cases (n = 45) and showed positive expression in 53.3% of tumors.
Lastly, we filtered the Fraction and Allele-Specific Copy Number Estimates from Tumor Sequencing (FACETS) results for loss-of-function and splice site mutations to interrogate for copy number alterations and loss of heterozygosity (LOH) in tumors with recurrent (≥ 3) alterations in ATM, BRCA1, NF1, PTEN, and RB1 genes. Most tumors with alterations in these genes further exhibited either loss, LOH or copy-neutral LOH (CN-LOH) in the other allele (Fig. 5c). There was a significant difference in the overall LOH status of TMB-high TNBCs when compared to the remaining TMB-high BCs (Chi-squared test: p = 0.0001). These findings warrant further exploration to determine the prognostic implications and clinical importance of such events.
Discussion
Here, we provide a comprehensive assessment of a large cohort of TMB-high BCs to characterize the genomic alterations that underpin this subset of tumors. We found a preponderance of APOBEC-related gene mutations involving PIK3CA, KMT2C, ARID1A, NF1, and CDH1 in our cohort that have been reportedly linked to endocrine resistance and metastases15,28. Moreover, loss-of-function ARID1A and PTEN gene mutations reported to be involved in immune cell exclusion were identified at a high frequency in our series. Given the FDA approval of pembrolizumab in the unresectable/metastatic setting for TMB-high solid tumors and the modest treatment responses to IC-blockade in BC, our findings provide insight into treatment plans to better target this group of tumors.
Prior evidence has associated APOBEC mutagenesis with higher TMB and to harbor mutations associated with immune cell exclusion in BC18,29,30. The APOBEC signature in conjunction with PIK3CA mutations is largely encountered in metastatic TNBCs, rendering these tumors amenable to direct agents, such as AKT inhibitors (e.g., ipatasertib, capivasertib), that target the PI3K/AKT pathway and may confer improved therapeutic response19,31. PTEN is a tumor suppressor that downregulates the PI3K/AKT signaling axis and is implicated in cellular processes such as proliferation, invasion, and survival32. Thus, abrogation of PTEN activity is linked to aberrant activation of PI3K/AKT signaling and tumorigenesis. We observed a predilection for driver PTEN alterations, mainly loss-of-function truncating and missense mutations, in ER+/HER2− TMB-high BCs (15%) and TMB-high TNBCs (28%) when compared to TMB-high HER2+ tumors (i.e., ER+/HER2+: 2%; ER−/HER2+: 3%). In addition, the predominance of PIK3CA p.E542K and p.E545K hotspot mutations, among others, further substantiates APOBEC-mediated effects and a predilection towards the PI3K/AKT pathway that may be amenable to pharmacologic abrogation. In keeping with this finding, recent evidence showed that APOBEC activity is present in pre-treatment tumor samples and is a mediator of therapeutic resistance, potentially serving as a biomarker for alternative therapies33.
Deregulation of various oncogenic signaling pathways has been identified to play key roles in immune cell exclusion in different tumor types. This in part, is also attributed to loss or gain-of-function mutations that are intricately linked to certain signaling modules. The archetype mechanism of immune exclusion was principally characterized in metastatic melanoma, whereby activation of the WNT/β-catenin pathway resulted in a lack of tumor-infiltrating T-cells in mouse models34,35. Multiple lines of evidence have shown that several fundamental BC genes are involved in tumor immune surveillance. The clinical importance of this is further compounded by the paucity of CD8+ T-cell infiltration in up to 57.6% of primary BCs36,37. Moreover, higher rates of metastasis with diminished patient survival are witnessed in BCs with a scarcity of CD8+ T-cells38,39,40.
Upregulation of genes related to T-cell activation, co-stimulation, and receptor signaling has been reported in TP53-wild type basal-like and ER− tumors with histopathologic immune cell infiltration29. In addition, other frequently altered genes encountered in BC have been linked with a lack of immunotherapeutic response. Diminished clinical response with reduced PFS and overall survival (OS) was observed in response to PD-1/PD-L1 treated metastatic TNBCs harboring loss-of-function mutations in PTEN30. A similar phenomenon is seen in PTEN-depleted metastatic melanomas with abrogation of T-cell infiltration. Interestingly, the latter study showed increased efficacy of IC-blockade upon treatment with a PI3Kβ inhibitor in mouse models41. These findings suggest critical roles for PTEN and the interplay between PI3K/AKT signaling and immune evasion.
Studies have found the acquisition of NF1 mutations in metastatic tumors with induction of resistance to anti-endocrine therapies in the setting of loss-of-function NF1 mutations in ER+ BCs42. Accordingly, loss of NF1 shows sequential activation of the mitogen-activated protein kinase (MAPK) signaling pathway. ARID1A, a constituent of the switch/sucrose non-fermentable (SWI/SNF) chromatin remodeling complex, is the most abundantly mutated gene among this multiplex and has been revealed to express genes related to IFN-γ signaling that draw effector T-cell infiltration43. More importantly, the latter study discerned that ARID1A mutations correlate with dismal outcomes among IC-blockade therapies irrespective of TMB. These findings not only shed light on the mechanisms of immune cell evasion in different tumor types but also support the notion of a more multifaceted tumor approach to combat cancer beyond a steadfast TMB value.
Querying for ESR1 alterations yielded interesting findings. Specifically, we observed an increased proportion of ESR1 p.E380Q mutations in TMB-high BCs, in contrast to other well-characterized resistance hotspot mutations. This observation has also been documented in a previous report with a TMB-high BC and APOBEC signature44. Enrichment in this resistance mutation may potentially infer a high TMB in BCs. Further interrogation of primary TMB-high BCs stratified according to biomarker status revealed a dominant APOBEC signature in > 50% of tumors (i.e., ER+/HER2−, ER+/HER2+, and ER−/HER2+), apart from TMB-high TNBCs. The latter subgroup displayed a more diverse repertoire of mutational signatures, with a dominant APOBEC signature seen in 12% of tumors (Fig. 5a). In addition, mutations concentrated within the ligand-binding domain of ERα, predominantly affecting amino acid residues p.Y537 and p.D538, have been coupled with constitutive receptor activation and BC proliferation45,46. Studies investigating APOBEC-induced mutagenesis resulting in the generation of amino acid changes (i.e., glutamate [E] > glutamine [Q]), have shown this event to occur in ESR1 p.E380Q and PIK3CA p.E453Q hotspot mutations15. These single-base substitutions are recurrently enriched in metastatic BCs; however, the etiology is undetermined at present.
Our findings are in keeping with other investigators, who report TMB-high tumors in the range of 5% of BCs along with a dominant APOBEC mutational process19. Yet, the latter study didn’t dissect the underlying genomic alterations that drive these tumors beyond enrichment of PIK3CA alterations in tumors with dominant APOBEC activity. The predominance of APOBEC in our series is further substantiated by mutational events in PIK3CA, KMT2C, ARID1A, NF1, and RB1. We particularly observed a preponderance of recurrent PIK3CA hotspot mutations (i.e., p.E542K and p.E545K; oncogenic, gain-of-function) in BCs with APOBEC activity, concordant with previous fingings47. In a smaller percentage of tumors, we further detected PIK3CA p.E453K (oncogenic, gain-of-function) and p.E726K APOBEC-associated events28. Moreover, deficiency of the methyltransferase KMT2C, which has been purported to promote APOBEC mutagenesis in different tumor types, was also frequent48. Likely oncogenic truncating APOBEC-mediated NF1 p.Q554* and p.Q1399* events were identified in 5 tumors and were mutually exclusive with ESR1 hotspot mutations, further corroborating APOBEC dominance16. In addition, the increase in DDR gene mutations in our study is in keeping with findings from a previous study49. Collectively, the contribution of HRD and MSI signatures in TMB-high BCs warrants further investigation in prospective studies.
Prior work has shown that metastatic TMB-high TNBCs treated with IC-blockade had a suboptimal OS when compared to other treatment strategies5. Primary phase III clinical trials investigating the efficacy of combined atezolizumab and nab-paclitaxel reported a prolongation in the median PFS (7.5 months) in patients with metastatic PD-L1+ TNBC when compared to placebo and nab-paclitaxel (5 months)50. This study piloted the expedited FDA approval of combination atezolizumab and paclitaxel for PD-L1+ locally advanced/metastatic TNBC based on results from the IMpassion130 trial. The succeeding IMpassion131 phase III trial51 failed to show a significant benefit in PFS and OS of statistical significance, ultimately resulting in the withdrawal of the agent. In the KEYNOTE-355 trial, the addition of pembrolizumab to chemotherapy in advanced metastatic TNBCs with a PD-L1 combined positive score (CPS) of ≥ 10 showed improved OS compared to chemotherapy52. In our study, retrospective review revealed that 16 and 38 patients received atezolizumab or pembrolizumab, respectively, at some timepoint during their treatment. Most were heavily pretreated patients who received adjuvant therapy and ultimately developed progression of disease with eventual demise (atezolizumab, n = 14; pembrolizumab, n = 21). While PD-L1+ and TMB-high tumors are used as predictive biomarkers for IC-blockade, only a subset of TMB-high BCs were PD-L1+ in our series. These findings suggest that alternate mechanisms may contribute to disease progression, given the lack of immunotherapeutic response despite harboring a high TMB, albeit in the metastatic setting.
Our study has some limitations. The retrospective nature of our study may be prone to selection bias, as many patients have been heavily pretreated prior to referral to our institution. In addition, a large proportion of tumors in our series were metastatic in nature, and limited cases had matched primary and metastatic tumors for clonal evolution analysis. Moreover, MSK-IMPACT is a targeted sequencing panel that may preclude the identification of genomic alterations not included in the panel. Yet, our study provides a comprehensive characterization of the largest TMB-high BC cohort to our knowledge, with novel insights that may help predict response to IC-blockade and other therapies.
In conclusion, the present study comprehensively characterizes the genomic landscape of TMB-high BCs, accompanied by mutational signature analyses that offer deeper insights into this subclass of BCs. The distribution of genomic events in these patients provides further groundwork for better-tailored therapies to improve therapeutic outcomes.
Methods
Case selection
The study was approved by the Memorial Sloan Kettering Cancer Center (MSKCC) Institutional Review Board (IRB) (Protocol #17-287) and has been performed in accordance with the Declaration of Helsinki. The requirement for written informed consent was waived as the study was retrospective, all data were de-identified, and the research contained no more than minimal risk to the participants or their privacy. All BCs that underwent clinical FDA-authorized tumor–normal targeted massively parallel sequencing analysis of up to 505 cancer-related genes by the MSK-IMPACT platform, from September 2014 to August 2022 (data freeze), were evaluated (n = 7894). Cases were filtered to identify those with a TMB threshold of ≥ 10 mut/Mb. In total, 527 TMB-high BCs (462 patients: n = 460, female; n = 2, male) were identified and included in the current study. Clinicopathologic data were collected from the electronic medical records at MSKCC. Patient age at diagnosis ranged from 28 to 82 years. Receptor information status (ER and HER2) was assessed on the BC samples that underwent genomic profiling.
MSK-IMPACT assay
Details of the MSK-IMPACT assay have been previously published53. Briefly, MSK-IMPACT is a comprehensive molecular profiling assay that involves hybridization capture and deep sequencing of all exons and selected introns of up to 505 oncogenes and tumor-suppressor genes, allowing the detection of point mutations, small insertions or deletions, and rearrangements. In addition to capturing all coding regions of the genes, the assay also captures > 1000 intergenic and intronic single-nucleotide polymorphisms (tiling probes), interspersed homogenously across the genome, aiding the accurate assessment of genome-wide copy number. In total, the probes target approximately 1.2 megabases of the human genome. The mean tumor sample coverage in the study was 623X (median: 617X). All alterations detected in select genes are shown.
Genomic DNA was extracted from formalin-fixed paraffin-embedded (FFPE) tumor tissue after manual macrodissection to ensure at least 10% tumor content. DNA input ranged from 100 to 200 ng, as measured by fluorometric methods. Matching peripheral blood (EDTA tube) from each patient was also extracted for use as a normal control. Sequence libraries were prepared (Kapa Biosystems, Wilmington, MA) through a series of enzymatic steps, including shearing of double-stranded DNA, end repair, A-base addition, ligation of bar-coded sequence adaptors, and low-cycle PCR amplification. Multiple bar-coded sequence libraries were pooled and captured using our custom-designed biotinylated probes (Roche NimbleGen, Madison, WI). Captured DNA fragments were sequenced on an Illumina HiSeq2500 (Illumina, San Diego, CA) as 100-bp paired-end reads that were then subjected to the bioinformatics analysis pipeline. Sequencing reads were aligned to the human genome (hg19) using Burrows-Wheeler Aligner software version 0.7.5a (http://arxiv.org/abs/1303.3997, last accessed October 1, 2013). ABRA54 was used for read realignment around indels, and Genome Analysis Toolkit55 was used for base quality score recalibration. Duplicate reads were marked and not used in the downstream analyses.
MSK-Fusion assay
The MSK-Fusion assay is a targeted RNA-based panel that utilizes the Archer Anchored Multiplex PCR (AMPTM) technology56 and next-generation sequencing to detect gene fusions and oncogenic isoforms in solid tumors57,58,59. The custom Archer-based MSK-Fusion panel includes up to 85 genes, including the kinase domains of the following genes: ALK, BRAF, EGFR, ERBB2, ERBB4, FGFR1, FGFR2, FGFR3, KIT, MET, NTRK1, NTRK2, NTRK3, RET, and ROS1. The MSK-Fusion panel included ESR1 as of October 2018. After DNA sequencing, BCs were referred to RNA sequencing during the period studied, including TNBCs with no driver alteration, and ER+ metastatic BCs progressing on therapy.
SigMA pipeline
SigMA is a signature analysis tool optimized to detect mutational signatures utilizing information from exomes and whole-genome sequencing13. Briefly, SigMA employs a likelihood-based matching approach whereby it associates a tumor mutational spectrum with tumor subtypes according to their signature composition, which is determined by clustering and is used as a reference. The likelihood of the sample to belong to each tumor subtype is calculated, followed by a multivariate analysis, which allows us to obtain a final score for the presence of a signature by combining likelihood and cosine similarity with a non-negative least squares algorithm. Mutational signatures were generated by considering all nonsynonymous mutations in tumors with ≥ 8 mutations. The latter number was determined and adopted by our sensitivity and specificity analysis. A non-parametric Wilcoxon Rank-Sum test (Mann–Whitney U test) was used for statistical analysis between different mutational signatures and TMB difference.
FACETS
Allele-specific copy number analysis and assessment of LOH were performed by the FACETS algorithm (https://github.com/mskcc/facets2n). Cases were reviewed for proper fitment, and those in which a tumor diploid state was not attainable were excluded from further analysis. TMB-high TNBCs with recurrent loss-of-function gene events (≥ 3) in key genes were further analyzed by FACETS and subsequently compared to the remaining TMB-high BCs that exhibited similar loss-of-function events in the same genes.
Immunohistochemical analysis
Immunohistochemistry for mismatch repair proteins (MLH1: clone ES05 [Leica Biosystems], 1:500 dilution; PMS2: clone A16.4 [556415], 1:100 dilution; MSH2: clone G219-1129 [Cell Marque], 1:750 dilution; MSH6: clone EP49 [Agilent], 1:500 dilution) were performed on select cases. Tumors with positive nuclear expression were classified as normal/retained protein expression. Tumors with loss of nuclear expression for any of the four proteins were classified as abnormal/absent protein expression.
PD-L1 status was assessed by immunohistochemistry using two different assays during the study period on locally advanced or metastatic TNBCs. PD-L1 clone SP142 IHC (ready-to-use) was performed as the companion diagnostic assay for atezolizumab, using Ventana Benchmark Ultra System (Ventana Medical Systems) with antibody detection using the OptiView DAB IHC Detection Kit (Ventana Medical Systems), according to the manufacturer’s manual60. PD-L1 SP142 positivity is defined as expression on stromal tumor-infiltrating immune cells occupying ≥ 1% of the tumor area as described previously61,62. PD-L1 clone SP263 IHC (ready-to-use) was performed to select patients for pembrolizumab treatment, using Ventana Benchmark Ultra System (Ventana Medical Systems) with antibody detection using the OptiView DAB IHC Detection Kit (Ventana Medical Systems). PD-L1 SP263 has been validated against the companion diagnostic assay PD-L1 22C3 pharmDx and found to be comparable63. PD-L1 SP263 is reported as a CPS, which is the number of PD-L1 staining cells (i.e., tumor cells, lymphocytes, and macrophages) divided by the total number of viable tumor cells, multiplied by 100. PD-L1 positivity is defined as a CPS ≥ 10.
TMB calculation
TMB was calculated for each individual patient by normalizing the total number of mutations detected in the MSK-IMPACT panel by its total exonic size in megabases.
Assessment of TILs
Primary TMB-high TNBCs were morphologically evaluated for the presence of TILs following recommendations by the International TILs Working Group25. Briefly, two pathologists (T.V. and D.S.R.) quantified the percentage of TILs that occupied the stromal tissue compartment within the borders of the invasive tumor (n = 22) in increments of 5%. TILs outside of the tumor borders and at the periphery of ductal carcinoma in situ (DCIS) were excluded. BCs with extensive fragmentation or within lymphoid tissue could not be evaluated and were excluded from assessment of TILs (n = 3).
Statistical analyses
Pearson’s Chi-squared test with Yates’ continuity correction was used for statistical comparisons of genomic alterations between TMB-high and non-TMB-high BCs. For comparing the difference in TMB across different mutational signatures, a non-parametric Wilcoxon Rank-Sum test (Mann–Whitney U test) was used. All tests of significance considered a p-value < 0.05 as statistically significant. Other analyses are specified within the manuscript.
Data availability
The MSK-IMPACT sequencing dataset is available through the cBioPortal for Cancer Genomics at www.cBioPortal.org.
Code availability
All software used in this manuscript is available online.
References
Marcus, L., Lemery, S. J., Keegan, P. & Pazdur, R. FDA Approval Summary: pembrolizumab for the treatment of microsatellite instability-high solid tumors. Clin. Cancer Res. 25, 3753–3758 (2019).
Marcus, L. et al. FDA Approval Summary: pembrolizumab for the treatment of tumor mutational burden-high solid tumors. Clin. Cancer Res. 27, 4685–4689 (2021).
Lawrence, M. S. et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature 499, 214–218 (2013).
Loi, S. et al. Prognostic and predictive value of tumor-infiltrating lymphocytes in a phase III randomized adjuvant breast cancer trial in node-positive breast cancer comparing the addition of docetaxel to doxorubicin with doxorubicin-based chemotherapy: BIG 02-98. J. Clin. Oncol. 31, 860–867 (2013).
McGrail, D. J. et al. High tumor mutation burden fails to predict immune checkpoint blockade response across all cancer types. Ann. Oncol. 32, 661–672 (2021).
Nanda, R. et al. Pembrolizumab in patients with advanced triple-negative breast cancer: Phase Ib KEYNOTE-012 Study. J. Clin. Oncol. 34, 2460–2467 (2016).
Winer, E. P. et al. Pembrolizumab versus investigator-choice chemotherapy for metastatic triple-negative breast cancer (KEYNOTE-119): a randomised, open-label, phase 3 trial. Lancet Oncol. 22, 499–511 (2021).
Zitvogel, L., Galluzzi, L., Smyth, M. J. & Kroemer, G. Mechanism of action of conventional and targeted anticancer therapies: reinstating immunosurveillance. Immunity 39, 74–88 (2013).
Adams, S. et al. Current landscape of immunotherapy in breast cancer: a review. JAMA Oncol. 5, 1205–1214 (2019).
Goodman, A. M. et al. Tumor mutational burden as an independent predictor of response to immunotherapy in diverse cancers. Mol. Cancer Ther. 16, 2598–2608 (2017).
Cha, S., Lee, E. & Won, H. H. Comprehensive characterization of distinct genetic alterations in metastatic breast cancer across various metastatic sites. NPJ Breast Cancer 7, 93 (2021).
Priedigkeit, N. et al. Intrinsic subtype switching and acquired ERBB2/HER2 amplifications and mutations in breast cancer brain metastases. JAMA Oncol. 3, 666–671 (2017).
Gulhan, D. C., Lee, J. J., Melloni, G. E. M., Cortés-Ciriano, I. & Park, P. J. Detecting the mutational signature of homologous recombination deficiency in clinical samples. Nat. Genet. 51, 912–919 (2019).
McGranahan, N. et al. Clonal status of actionable driver events and the timing of mutational processes in cancer evolution. Sci. Transl. Med. 7, 283ra254 (2015).
Bos, M. K., Smid, M., Sleijfer, S. & Martens, J. W. M. Apolipoprotein B mRNA-editing catalytic polypeptide-like-induced protein changes in estrogen receptor-positive, human epidermal growth factor receptor 2-negative breast cancer throughout disease progression. JCO Precis. Oncol. 6, e2100190 (2022).
Sokol, E. S. et al. Loss of function of NF1 is a mechanism of acquired resistance to endocrine therapy in lobular breast cancer. Ann. Oncol. 30, 115–123 (2019).
Savas, P. et al. Correction: the subclonal architecture of metastatic breast cancer: results from a prospective community-based rapid autopsy program “CASCADE”. PLoS Med. 14, e1002302 (2017).
Jakobsdottir, G. M., Brewer, D. S., Cooper, C., Green, C. & Wedge, D. C. APOBEC3 mutational signatures are associated with extensive and diverse genomic instability across multiple tumour types. BMC Biol. 20, 117 (2022).
Barroso-Sousa, R. et al. Prevalence and mutational determinants of high tumor mutation burden in breast cancer. Ann. Oncol. 31, 387–394 (2020).
Razavi, P. et al. The genomic landscape of endocrine-resistant advanced breast cancers. Cancer Cell 34, 427–438.e426 (2018).
Fu, X. et al. FOXA1 upregulation promotes enhancer and transcriptional reprogramming in endocrine-resistant breast cancer. Proc. Natl Acad. Sci. USA 116, 26823–26834 (2019).
Robson, M. E. et al. OlympiAD final overall survival and tolerability results: Olaparib versus chemotherapy treatment of physician’s choice in patients with a germline BRCA mutation and HER2-negative metastatic breast cancer. Ann. Oncol. 30, 558–566 (2019).
Litton, J. K. et al. Talazoparib versus chemotherapy in patients with germline BRCA1/2-mutated HER2-negative advanced breast cancer: final overall survival results from the EMBRACA trial. Ann. Oncol. 31, 1526–1535 (2020).
Ghosh, M. et al. Mutant p53 suppresses innate immune signaling to promote tumorigenesis. Cancer Cell 39, 494–508.e495 (2021).
Salgado, R. et al. The evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer: recommendations by an International TILs Working Group 2014. Ann. Oncol. 26, 259–271 (2015).
Loi, S. et al. Tumor-infiltrating lymphocytes and prognosis: a pooled individual patient analysis of early-stage triple-negative breast cancers. J. Clin. Oncol. 37, 559–569 (2019).
Manzano, R. G., Catalan-Latorre, A. & Brugarolas, A. RB1 and TP53 co-mutations correlate strongly with genomic biomarkers of response to immunity checkpoint inhibitors in urothelial bladder cancer. BMC Cancer 21, 432 (2021).
Roelofs, P. A., Martens, J. W. M., Harris, R. S. & Span, P. N. Clinical implications of APOBEC3-mediated mutagenesis in breast cancer. Clin. Cancer Res 29, 1658–1669 (2023).
Quigley, D. et al. Lymphocyte invasion in IC10/basal-like breast tumors is associated with wild-type TP53. Mol. Cancer Res. 13, 493–501 (2015).
Barroso-Sousa, R. et al. Tumor mutational burden and PTEN alterations as molecular correlates of response to PD-1/L1 blockade in metastatic triple-negative breast cancer. Clin. Cancer Res. 26, 2565–2572 (2020).
Xing, Y. et al. Phase II trial of AKT inhibitor MK-2206 in patients with advanced breast cancer who have tumors with PIK3CA or AKT mutations, and/or PTEN loss/PTEN mutation. Breast Cancer Res. 21, 78 (2019).
Carbognin, L., Miglietta, F., Paris, I. & Dieci, M. V. Prognostic and predictive implications of PTEN in breast cancer: unfulfilled promises but intriguing perspectives. Cancers (Basel) 11, 1401 (2019).
Gupta, A. et al. APOBEC3 mutagenesis drives therapy resistance in breast cancer. Nat. Genet. 57, 1452–1462 (2025).
Spranger, S., Dai, D., Horton, B. & Gajewski, T. F. Tumor-residing Batf3 dendritic cells are required for effector T cell trafficking and adoptive T cell therapy. Cancer Cell 31, 711–723.e714 (2017).
Spranger, S., Bao, R. & Gajewski, T. F. Melanoma-intrinsic β-catenin signalling prevents anti-tumour immunity. Nature 523, 231–235 (2015).
Liu, S. et al. Prognostic significance of FOXP3+ tumor-infiltrating lymphocytes in breast cancer depends on estrogen receptor and human epidermal growth factor receptor-2 expression status and concurrent cytotoxic T-cell infiltration. Breast Cancer Res. 16, 432 (2014).
Mahmoud, S. M. et al. Tumor-infiltrating CD8+ lymphocytes predict clinical outcome in breast cancer. J. Clin. Oncol. 29, 1949–1955 (2011).
Coffelt, S. B. et al. IL-17-producing γδ T cells and neutrophils conspire to promote breast cancer metastasis. Nature 522, 345–348 (2015).
Bidwell, B. N. et al. Silencing of Irf7 pathways in breast cancer cells promotes bone metastasis through immune escape. Nat. Med. 18, 1224–1231 (2012).
Ali, H. R. et al. Association between CD8+ T-cell infiltration and breast cancer survival in 12,439 patients. Ann. Oncol. 25, 1536–1543 (2014).
Peng, W. et al. Loss of PTEN promotes resistance to T cell-mediated immunotherapy. Cancer Discov. 6, 202–216 (2016).
Pearson, A. et al. Inactivating NF1 mutations are enriched in advanced breast cancer and contribute to endocrine therapy resistance. Clin. Cancer Res. 26, 608–622 (2020).
Li, J. et al. Epigenetic driver mutations in ARID1A shape cancer immune phenotype and immunotherapy. J. Clin. Investig. 130, 2712–2726 (2020).
Chumsri, S. et al. Durable complete response with immune checkpoint inhibitor in breast cancer with high tumor mutational burden and APOBEC signature. J. Natl Compr. Cancer Netw. 18, 517–521 (2020).
Chandarlapaty, S. et al. Prevalence of ESR1 mutations in cell-free DNA and outcomes in metastatic breast cancer: a secondary analysis of the BOLERO-2 Clinical Trial. JAMA Oncol. 2, 1310–1315 (2016).
Toy, W. et al. ESR1 ligand-binding domain mutations in hormone-resistant breast cancer. Nat. Genet 45, 1439–1445 (2013).
Wong, J. K. L. et al. Association of mutation signature effectuating processes with mutation hotspots in driver genes and non-coding regions. Nat. Commun. 13, 178 (2022).
Hu, X., Biswas, A. & De, S. KMT2C-deficient tumors have elevated APOBEC mutagenesis and genomic instability in multiple cancers. NAR Cancer 4, zcac023 (2022).
Mei, P. et al. High tumor mutation burden is associated with DNA damage repair gene mutation in breast carcinomas. Diagn. Pathol. 15, 50 (2020).
Schmid, P. et al. Atezolizumab and nab-paclitaxel in advanced triple-negative breast cancer. N. Engl. J. Med. 379, 2108–2121 (2018).
Miles, D. et al. Primary results from IMpassion131, a double-blind, placebo-controlled, randomised phase III trial of first-line paclitaxel with or without atezolizumab for unresectable locally advanced/metastatic triple-negative breast cancer. Ann. Oncol. 32, 994–1004 (2021).
Cortes, J. et al. Pembrolizumab plus chemotherapy in advanced triple-negative breast cancer. N. Engl. J. Med. 387, 217–226 (2022).
Cheng, D. T. et al. Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT): a hybridization capture-based next-generation sequencing clinical assay for solid tumor molecular oncology. J. Mol. Diagn. 17, 251–264 (2015).
Mose, L. E., Wilkerson, M. D., Hayes, D. N., Perou, C. M. & Parker, J. S. ABRA: improved coding indel detection via assembly-based realignment. Bioinformatics 30, 2813–2815 (2014).
McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).
Zheng, Z. et al. Anchored multiplex PCR for targeted next-generation sequencing. Nat. Med. 20, 1479–1484 (2014).
Zhu, G. et al. Diagnosis of known sarcoma fusions and novel fusion partners by targeted RNA sequencing with identification of a recurrent ACTB-FOSB fusion in pseudomyogenic hemangioendothelioma. Mod. Pathol. 32, 609–620 (2019).
Benayed, R. et al. High yield of RNA sequencing for targetable kinase fusions in lung adenocarcinomas with no mitogenic driver alteration detected by DNA sequencing and low tumor mutation burden. Clin. Cancer Res. 25, 4712–4722 (2019).
Ferguson, D. C. et al. Androgen receptor splice variant-7 in breast cancer: clinical and pathologic correlations. Mod. Pathol. 35, 396–402 (2022).
Reis, H. et al. PD-L1 expression in urothelial carcinoma with predominant or pure variant histology: concordance among 3 commonly used and commercially available antibodies. Am. J. Surg. Pathol. 43, 920–927 (2019).
Hoda, R. S. et al. Clinical and pathologic features associated with PD-L1 (SP142) expression in stromal tumor-infiltrating immune cells of triple-negative breast carcinoma. Mod. Pathol. 33, 2221–2232 (2020).
Hoda, R. S. et al. Interobserver variation of PD-L1 SP142 immunohistochemistry interpretation in breast carcinoma: a study of 79 cases using whole slide imaging. Arch. Pathol. Lab. Med. 145, 1132–1137 (2021).
Kim, S. Y. et al. Comprehensive comparison of 22C3 and SP263 PD-L1 expression in non-small-cell lung cancer using routine clinical and conditioned archives. Cancers (Basel) 14, 3138 (2022).
Acknowledgements
This research was funded in part through the NIH/NCI Cancer Center Support Grant P30 CA008748 and supported by the Marie-Josée and Henry R. Kravis Center for Molecular Oncology. F.P. is funded in part by an NIH/NCI P50 CA247749 01 grant and by a STARR Consortium grant.
Author information
Authors and Affiliations
Contributions
T.V.: conceptualization, data curation, formal analysis, investigation, methodology, writing—original draft and editing; C.V., S.R., A.M.: data curation, formal analysis, investigation, methodology, writing—review and editing; F.P., E.B., C.S., M.E.A., M.L.: data curation, resources, writing—review and editing; H.Y.W.: conceptualization, data curation, investigation, writing— review and editing; D.S.R.: conceptualization, data curation, formal analysis, investigation, writing—review and editing. All authors read and approved the final version of the manuscript.
Corresponding author
Ethics declarations
Competing interests
C.V.: reports equity, intellectual property rights, professional services, and activities (uncompensated) from Paige. AI, Inc. (outside of the submitted work). F.P.: reports membership of the scientific advisory board of MultiplexDx, reports consultancy fees for AstraZeneca, and is a member of their diagnostic advisory board (outside of the submitted work). M.E.A.: reports consulting for Janssen Global Services, Bristol-Myers Squibb, AstraZeneca, Roche, Merck, and Biocartis (outside of the submitted work). M.L.: reports having received honoraria for advisory board participation from Merck, AstraZeneca, Bayer, stock options for advisory board participation from Paige. AI, Inc., and research support from LOXO Oncology, Merus, Elevation Oncology, Helsinn Healthcare SA, ADC Therapeutics, and Rain Oncology (outside of the submitted work). In addition, M.L. is eligible for royalties from a license agreement between MSKCC and Sophia Genetics concerning MSK-IMPACT (outside of the submitted work). H.Y.W. reports personal fees from AstraZeneca and Daiichi Sankyo (outside of the submitted work). D.S.R. reports personal fees from AstraZeneca and Daiichi Sankyo (outside of the submitted work). The rest of the authors declare no potential conflicts of interest.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Vougiouklakis, T., Vanderbilt, C., Rana, S. et al. Genomic characterization of tumor mutational burden-high breast carcinomas. npj Precis. Onc. 9, 277 (2025). https://doi.org/10.1038/s41698-025-01045-x
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41698-025-01045-x
