Geographic variation of mutagenic exposures in kidney cancer genomes.

International differences in the incidence of many cancer types indicate the existence of carcinogen exposures that have not yet been identified by conventional epidemiology make a substantial contribution to cancer burden1. In clear cell renal cell carcinoma, obesity, hypertension and tobacco smoking are risk factors, but they do not explain the geographical variation in its incidence2. Underlying causes can be inferred by sequencing the genomes of cancers from populations with different incidence rates and detecting differences in patterns of somatic mutations. Here we sequenced 962 clear cell renal cell carcinomas from 11 countries with varying incidence. The somatic mutation profiles differed between countries. In Romania, Serbia and Thailand, mutational signatures characteristic of aristolochic acid compounds were present in most cases, but these were rare elsewhere. In Japan, a mutational signature of unknown cause was found in more than 70% of cases but in less than 2% elsewhere. A further mutational signature of unknown cause was ubiquitous but exhibited higher mutation loads in countries with higher incidence rates of kidney cancer. Known signatures of tobacco smoking correlated with tobacco consumption, but no signature was associated with obesity or hypertension, suggesting that non-mutagenic mechanisms of action underlie these risk factors. The results of this study indicate the existence of multiple, geographically variable, mutagenic exposures that potentially affect tens of millions of people and illustrate the opportunities for new insights into cancer causation through large-scale global cancer genomics.

Validation of the Prognostic Performance of Breast Cancer Index in Hormone Receptor-Positive Postmenopausal Breast Cancer Patients in the TEAM Trial.

PURPOSE: Patients with early-stage hormone receptor-positive (HR+) breast cancer face a prolonged risk of recurrence even after adjuvant endocrine therapy. The Breast Cancer Index (BCI) is significantly prognostic for overall (0-10 years) and late (5-10 years) distant recurrence (DR) risk in N0 and N1 patients. Here, BCI prognostic performance was evaluated in HR+ postmenopausal women from the Tamoxifen and Exemestane Adjuvant Multinational (TEAM) trial. EXPERIMENTAL DESIGN: 3,544 patients were included in the analysis (N = 1,519 N0, N = 2,025 N+). BCI risk groups were calculated using pre-specified cutoff points. Kaplan-Meier analyses and log-rank tests were used to assess the prognostic significance of BCI risk groups based on DR. Hazard ratios (HR) and confidence intervals (CI) were calculated using Cox models with and without clinical covariates. RESULTS: For overall 10-year DR, BCI was significantly prognostic in Ni0 (N = 1,196) and N1 (N = 1,234) patients who did not receive prior chemotherapy (P < 0.001). In patients who were DR-free for 5 years, 10-year late DR rates for low- and high-risk groups were 5.4% and 9.3% (N0 cohort, N = 1,285) and 4.8% and 12.2% (N1 cohort, N = 1,625) with multivariate HRs of 2.25 (95% CI, 1.30-3.88; P = 0.004) and 2.67 (95% CI, 1.53-4.63; P < 0.001), respectively. Late DR performance was substantially improved using previously optimized cutoff points, identifying BCI low-risk groups with even lower 10-year late DR rates of 3.8% and 2.7% in N0 and N1 patients, respectively. CONCLUSIONS: The TEAM trial represents the largest prognostic validation study for BCI to date and provides a more representative assessment of late DR risk to guide individualized treatment decision-making for HR+ patients with early-stage breast cancer.

A DNA copy number alteration classifier as a prognostic tool for prostate cancer patients.

BACKGROUND: Distinguishing between true indolent and potentially life-threatening prostate cancer is challenging in tumours displaying clinicopathologic features associated with low or intermediate risk of relapse. Several somatic DNA copy number alterations (CNAs) have been identified as potential prognostic biomarkers, but the standard cytogenetic method to assess them has a limited multiplexing capability. METHODS: Multiplex ligation-dependent probe amplification (MLPA) targeting 14 genes was optimised to survey 448 tumours of patients with low or intermediate risk (Grade Group 1-3, Gleason score ≤7) who underwent radical prostatectomy. A 6-gene CNA classifier was developed using random survival forest and Cox proportional hazard modelling to predict biochemical recurrence. RESULTS: The classifier score was significantly associated with biochemical recurrence after adjusting for standard clinicopathologic variables and the known prognostic index CAPRA-S score with a hazard ratio of 2.17 and 1.80, respectively (n = 406, P < 0.01). The prognostic value of this classifier was externally validated in published CNA data from three radical prostatectomy cohorts and one radiation therapy pre-treatment biopsy cohort. CONCLUSION: The 6-gene CNA classifier generated by a single MLPA assay compatible with the small quantities of DNA extracted from formalin-fixed paraffin-embedded (FFPE) tissue specimens has the potential to improve the clinical management of patients with low or intermediate risk disease.

Correlative studies of the Breast Cancer Index (HOXB13/IL17BR) and ER, PR, AR, AR/ER ratio and Ki67 for prediction of extended endocrine therapy benefit: a Trans-aTTom study.

BACKGROUND: Multiple clinical trials demonstrate consistent but modest benefit of adjuvant extended endocrine therapy (EET) in HR + breast cancer patients. Predictive biomarkers to identify patients that benefit from EET are critical to balance modest reductions in risk against potential side effects of EET. This study compares the performance of the Breast Cancer Index, BCI (HOXB13/IL17BR, H/I), with expression of estrogen (ER), progesterone (PR), and androgen receptors (AR), and Ki67, for prediction of EET benefit. METHODS: Node-positive (N+) patients from the Trans-aTTom study with available tissue specimen and BCI results (N = 789) were included. Expression of ER, PR, AR, and Ki67 was assessed by quantitative immunohistochemistry. BCI (H/I) gene expression analysis was conducted by quantitative RT-PCR. Statistical significance of the treatment by biomarker interaction was evaluated by likelihood ratio tests based on multivariate Cox proportional models, adjusting for age, tumor size, grade, and HER2 status. Pearson's correlation coefficients were calculated to evaluate correlations between BCI (H/I) versus ER, PR, AR, Ki67 and AR/ER ratio. RESULTS: EET benefit, measured by the difference in risk of recurrence between patients treated with tamoxifen for 10 versus 5 years, is significantly associated with increasing values of BCI (H/I) (interaction P = 0.01). In contrast, expression of ER (P = 0.83), PR (P = 0.66), AR (P = 0.78), Ki67 (P = 0.87) and AR/ER ratio (P = 0.84) exhibited no significant relationship with EET benefit. BCI (H/I) showed a very weak negative correlation with ER (r = - 0.18), PR (r = - 0.25), and AR (r = - 0.14) expression, but no correlation with either Ki67 (r = 0.04) or AR/ER ratio (r = 0.02). CONCLUSION: These findings are consistent with the growing body of evidence that BCI (H/I) is significantly predictive of response to EET and outcome. Results from this direct comparison demonstrate that expression of ER, PR, AR, Ki67 or AR/ER ratio are not predictive of benefit from EET. BCI (H/I) is the only clinically validated biomarker that predicts EET benefit.

Selecting patients with HER2-low breast cancer: Getting out of the tangle.

The promising effect of antibody-drug conjugates on breast cancer with low expression of HER2 (HER2-low) raises many questions regarding the optimal selection of patients for this treatment. A key question is whether HER2 immunohistochemistry, an assay optimised to detect HER2 amplification, is reliable enough to assess HER2 protein levels to select patients with HER2-low breast cancer in daily pathology practices worldwide. Moreover, whether this assessment can be performed with sufficient reproducibility between pathologists in daily practices is debatable. Herein, we address the historical track record of the CAP-ASCO HER2 Guidelines, the reported limited reproducibility by pathologists of HER2 immunohistochemistry in the non-amplified cases, and the performance variation of different antibodies. Based on this summary, we propose solutions to improve the robustness to enable reliable identification of patients with HER2-low breast cancer.

Systematically higher Ki67 scores on core biopsy samples compared to corresponding resection specimen in breast cancer: a multi-operator and multi-institutional study.

Ki67 has potential clinical importance in breast cancer but has yet to see broad acceptance due to inter-laboratory variability. Here we tested an open source and calibrated automated digital image analysis (DIA) platform to: (i) investigate the comparability of Ki67 measurement across corresponding core biopsy and resection specimen cases, and (ii) assess section to section differences in Ki67 scoring. Two sets of 60 previously stained slides containing 30 core-cut biopsy and 30 corresponding resection specimens from 30 estrogen receptor-positive breast cancer patients were sent to 17 participating labs for automated assessment of average Ki67 expression. The blocks were centrally cut and immunohistochemically (IHC) stained for Ki67 (MIB-1 antibody). The QuPath platform was used to evaluate tumoral Ki67 expression. Calibration of the DIA method was performed as in published studies. A guideline for building an automated Ki67 scoring algorithm was sent to participating labs. Very high correlation and no systematic error (p = 0.08) was found between consecutive Ki67 IHC sections. Ki67 scores were higher for core biopsy slides compared to paired whole sections from resections (p ≤ 0.001; median difference: 5.31%). The systematic discrepancy between core biopsy and corresponding whole sections was likely due to pre-analytical factors (tissue handling, fixation). Therefore, Ki67 IHC should be tested on core biopsy samples to best reflect the biological status of the tumor.

Discordance between Immunohistochemistry and Erb-B2 Receptor Tyrosine Kinase 2 mRNA to Determine Human Epidermal Growth Factor Receptor 2 Low Status for Breast Cancer.

Novel human epidermal growth factor receptor 2 (HER2)-directed antibody-drug conjugates have demonstrated efficacy in HER2-low expressing breast cancers, which are currently defined as those with immunohistochemistry (IHC) scores of 1+ or 2+ with a negative in situ hybridization assay. However, current HER2 testing methods are designed to identify HER2-amplified tumors with high expression levels. The true definition of HER2-low expressing breast cancers remains controversial. Using quantitative molecular analysis of breast cancers based on RNA expression, the dynamic range of HER2 expression exceeds that detected by in situ IHC approaches. Erb-B2 receptor tyrosine kinase 2 (ERBB2) mRNA expression levels across IHC groups using patient samples derived from the Tamoxifen Exemestane Adjuvant Multicenter Trial were investigated. The standardized mean differences in ERBB2 mRNA scores in log base 2 are 0.47 (95% CI, 0.36-0.57), 0.58 (95% CI, 0.26-0.70), and 0.32 (95% CI, -0.12 to 0.75) when comparing IHC 0+ without staining versus IHC 0+ with some staining, IHC 0+ with some staining versus IHC 1+, and IHC 1+ versus IHC 2+/fluorescence in situ hybridization-negative, respectively. The results showed immunohistochemical methods have a comparatively limited dynamic range for measuring HER2 protein expression. The range of expression based on RNA abundance suggests a molecular method defining HER2-low cancers may better serve the treatment decision needs of this group. Indeed, the validity of RNA abundance to identify HER2-low cancers and predict treatment response needs to be further evaluated by prospective clinical trials.

Breast Cancer Index Is a Predictive Biomarker of Treatment Benefit and Outcome from Extended Tamoxifen Therapy: Final Analysis of the Trans-aTTom Study.

PURPOSE: The Breast Cancer Index (BCI) HOXB13/IL17BR (H/I) ratio predicts benefit from extended endocrine therapy in hormone receptor-positive (HR+) early-stage breast cancer. Here, we report the final analysis of the Trans-aTTom study examining BCI (H/I)'s predictive performance. EXPERIMENTAL DESIGN: BCI results were available for 2,445 aTTom trial patients. The primary endpoint of recurrence-free interval (RFI) and secondary endpoints of disease-free interval (DFI) and disease-free survival (DFS) were examined using Cox proportional hazards regression and log-rank test. RESULTS: Final analysis of the overall study population (N = 2,445) did not show a significant improvement in RFI with extended tamoxifen [HR, 0.90; 95% confidence interval (CI), 0.69-1.16; P = 0.401]. Both the overall study population and N0 group were underpowered due to the low event rate in the N0 group. In a pre-planned analysis of the N+ subset (N = 789), BCI (H/I)-High patients derived significant benefit from extended tamoxifen (9.7% absolute benefit: HR, 0.33; 95% CI, 0.14-0.75; P = 0.016), whereas BCI (H/I)-Low patients did not (-1.2% absolute benefit; HR, 1.11; 95% CI, 0.76-1.64; P = 0.581). A significant treatment-to-biomarker interaction was demonstrated on the basis of RFI, DFI, and DFS (P = 0.037, 0.040, and 0.025, respectively). BCI (H/I)-High patients remained predictive of benefit from extended tamoxifen in the N+/HER2- subgroup (9.4% absolute benefit: HR, 0.35; 95% CI, 0.15-0.81; P = 0.047). A three-way interaction evaluating BCI (H/I), treatment, and HER2 status was not statistically significant (P = 0.849). CONCLUSIONS: Novel findings demonstrate that BCI (H/I) significantly predicts benefit from extended tamoxifen in HR+ N+ patients with HER2- disease. Moreover, BCI (H/I) demonstrates significant treatment to biomarker interaction across survival outcomes.

Upregulation of IFNÉ£-mediated chemokines dominate the immune transcriptome of muscle-invasive urothelial carcinoma.

Tumor inflammation is prognostically significant in high-grade muscle-invasive bladder cancer (MIBC). However, the underlying mechanisms remain elusive. To identify inflammation-associated immune gene expression patterns, we performed transcriptomic profiling of 40 MIBC archival tumors using the NanoString nCounter Human v.1.1 PanCancer Panel. Findings were validated using the TCGA MIBC dataset. Unsupervised and supervised clustering identified a distinctive immune-related gene expression profile for inflammation, characterized by significant upregulation of 149 genes, particularly chemokines, a subset of which also had potential prognostic utility. Some of the most enriched biological processes were lymphocyte activation and proliferation, leukocyte adhesion and migration, antigen processing and presentation and cellular response to IFN-γ. Upregulation of numerous IFN-γ-inducible chemokines, class II MHC molecules and immune checkpoint genes was detected as part of the complex immune response to MIBC. Further, B-cell markers linked to tertiary lymphoid structures were upregulated, which in turn is predictive of tumor response to immunotherapy and favorable outcome. Our findings of both an overall activated immune profile and immunosuppressive microenvironment provide novel insights into the complex immune milieu of MIBC with inflammation and supports its clinical significance for predicting prognosis and immunotherapeutic responsiveness, which warrants further investigation. This may open novel opportunities to identify mechanisms for developing new immunotherapeutic strategies.

Incorporation of TILs in daily breast cancer care: how much evidence can we bear?

One of the most important developments in the breast cancer field has been an improved understanding of prognostic and predictive biomarkers, of which TILs are increasingly gaining importance. The evaluation of TILs by light microscopy on a H&E-stained section is workable in a daily practice setting. Reproducibility of reporting TILs is good, but heterogeneity is a cause of variation. TILs provide clinicians with important prognostic information for patients with TNBC, as early-stage TNBC with high TILs have > 98% 5-year survival and TILs predict benefit to immunotherapy. Importantly, while TILs do not have level of evidence IA, TILs should be used as a prognostic factor with caution and with other accepted prognostic variables, such as tumour size and lymph node status, to inform clinicians and patients on their treatment options. A framework on how to use the TILs in daily practice is proposed, including a co-assessment with PD-L1 for its predictive role to immunotherapy.

Residual cancer burden after neoadjuvant chemotherapy and long-term survival outcomes in breast cancer: a multicentre pooled analysis of 5161 patients.

BACKGROUND: Previous studies have independently validated the prognostic relevance of residual cancer burden (RCB) after neoadjuvant chemotherapy. We used results from several independent cohorts in a pooled patient-level analysis to evaluate the relationship of RCB with long-term prognosis across different phenotypic subtypes of breast cancer, to assess generalisability in a broad range of practice settings. METHODS: In this pooled analysis, 12 institutes and trials in Europe and the USA were identified by personal communications with site investigators. We obtained participant-level RCB results, and data on clinical and pathological stage, tumour subtype and grade, and treatment and follow-up in November, 2019, from patients (aged ≥18 years) with primary stage I-III breast cancer treated with neoadjuvant chemotherapy followed by surgery. We assessed the association between the continuous RCB score and the primary study outcome, event-free survival, using mixed-effects Cox models with the incorporation of random RCB and cohort effects to account for between-study heterogeneity, and stratification to account for differences in baseline hazard across cancer subtypes defined by hormone receptor status and HER2 status. The association was further evaluated within each breast cancer subtype in multivariable analyses incorporating random RCB and cohort effects and adjustments for age and pretreatment clinical T category, nodal status, and tumour grade. Kaplan-Meier estimates of event-free survival at 3, 5, and 10 years were computed for each RCB class within each subtype. FINDINGS: We analysed participant-level data from 5161 patients treated with neoadjuvant chemotherapy between Sept 12, 1994, and Feb 11, 2019. Median age was 49 years (IQR 20-80). 1164 event-free survival events occurred during follow-up (median follow-up 56 months [IQR 0-186]). RCB score was prognostic within each breast cancer subtype, with higher RCB score significantly associated with worse event-free survival. The univariable hazard ratio (HR) associated with one unit increase in RCB ranged from 1·55 (95% CI 1·41-1·71) for hormone receptor-positive, HER2-negative patients to 2·16 (1·79-2·61) for the hormone receptor-negative, HER2-positive group (with or without HER2-targeted therapy; p<0·0001 for all subtypes). RCB score remained prognostic for event-free survival in multivariable models adjusted for age, grade, T category, and nodal status at baseline: the adjusted HR ranged from 1·52 (1·36-1·69) in the hormone receptor-positive, HER2-negative group to 2·09 (1·73-2·53) in the hormone receptor-negative, HER2-positive group (p<0·0001 for all subtypes). INTERPRETATION: RCB score and class were independently prognostic in all subtypes of breast cancer, and generalisable to multiple practice settings. Although variability in hormone receptor subtype definitions and treatment across patients are likely to affect prognostic performance, the association we observed between RCB and a patient's residual risk suggests that prospective evaluation of RCB could be considered to become part of standard pathology reporting after neoadjuvant therapy. FUNDING: National Cancer Institute at the US National Institutes of Health.

Multi-omic machine learning predictor of breast cancer therapy response.

Breast cancers are complex ecosystems of malignant cells and the tumour microenvironment1. The composition of these tumour ecosystems and interactions within them contribute to responses to cytotoxic therapy2. Efforts to build response predictors have not incorporated this knowledge. We collected clinical, digital pathology, genomic and transcriptomic profiles of pre-treatment biopsies of breast tumours from 168 patients treated with chemotherapy with or without HER2 (encoded by ERBB2)-targeted therapy before surgery. Pathology end points (complete response or residual disease) at surgery3 were then correlated with multi-omic features in these diagnostic biopsies. Here we show that response to treatment is modulated by the pre-treated tumour ecosystem, and its multi-omics landscape can be integrated in predictive models using machine learning. The degree of residual disease following therapy is monotonically associated with pre-therapy features, including tumour mutational and copy number landscapes, tumour proliferation, immune infiltration and T cell dysfunction and exclusion. Combining these features into a multi-omic machine learning model predicted a pathological complete response in an external validation cohort (75 patients) with an area under the curve of 0.87. In conclusion, response to therapy is determined by the baseline characteristics of the totality of the tumour ecosystem captured through data integration and machine learning. This approach could be used to develop predictors for other cancers.

The tale of TILs in breast cancer: A report from The International Immuno-Oncology Biomarker Working Group.

The advent of immune-checkpoint inhibitors (ICI) in modern oncology has significantly improved survival in several cancer settings. A subgroup of women with breast cancer (BC) has immunogenic infiltration of lymphocytes with expression of programmed death-ligand 1 (PD-L1). These patients may potentially benefit from ICI targeting the programmed death 1 (PD-1)/PD-L1 signaling axis. The use of tumor-infiltrating lymphocytes (TILs) as predictive and prognostic biomarkers has been under intense examination. Emerging data suggest that TILs are associated with response to both cytotoxic treatments and immunotherapy, particularly for patients with triple-negative BC. In this review from The International Immuno-Oncology Biomarker Working Group, we discuss (a) the biological understanding of TILs, (b) their analytical and clinical validity and efforts toward the clinical utility in BC, and (c) the current status of PD-L1 and TIL testing across different continents, including experiences from low-to-middle-income countries, incorporating also the view of a patient advocate. This information will help set the stage for future approaches to optimize the understanding and clinical utilization of TIL analysis in patients with BC.

Interobserver Agreement of PD-L1/SP142 Immunohistochemistry and Tumor-Infiltrating Lymphocytes (TILs) in Distant Metastases of Triple-Negative Breast Cancer: A Proof-of-Concept Study. A Report on Behalf of the International Immuno-Oncology Biomarker Working Group.

Patients with advanced triple-negative breast cancer (TNBC) benefit from treatment with atezolizumab, provided that the tumor contains ≥1% of PD-L1/SP142-positive immune cells. Numbers of tumor-infiltrating lymphocytes (TILs) vary strongly according to the anatomic localization of TNBC metastases. We investigated inter-pathologist agreement in the assessment of PD-L1/SP142 immunohistochemistry and TILs. Ten pathologists evaluated PD-L1/SP142 expression in a proficiency test comprising 28 primary TNBCs, as well as PD-L1/SP142 expression and levels of TILs in 49 distant TNBC metastases with various localizations. Interobserver agreement for PD-L1 status (positive vs. negative) was high in the proficiency test: the corresponding scores as percentages showed good agreement with the consensus diagnosis. In TNBC metastases, there was substantial variability in PD-L1 status at the individual patient level. For one in five patients, the chance of treatment was essentially random, with half of the pathologists designating them as positive and half negative. Assessment of PD-L1/SP142 and TILs as percentages in TNBC metastases showed poor and moderate agreement, respectively. Additional training for metastatic TNBC is required to enhance interobserver agreement. Such training, focusing on metastatic specimens, seems worthwhile, since the same pathologists obtained high percentages of concordance (ranging from 93% to 100%) on the PD-L1 status of primary TNBCs.

Heterogeneity of Circulating Tumor Cell-Associated Genomic Gains in Breast Cancer and Its Association with the Host Immune Response.

Tumor cells that preferentially enter circulation include the precursors of metastatic cancer. Previously, we characterized circulating tumor cells (CTC) from patients with breast cancer and identified a signature of genomic regions with recurrent copy-number gains. Through FISH, we now show that these CTC-associated regions are detected within the matched untreated primary tumors of these patients (21% to 69%, median 55.5%, n = 19). Furthermore, they are more prevalent in the metastases of patients who died from breast cancer after multiple rounds of treatment (70% to 100%, median 93%, samples n = 41). Diversity indices revealed that higher spatial heterogeneity for these regions within primary tumors is associated with increased dissemination and metastasis. An identified subclone with multiple regions gained (MRG clone) was enriched in a posttreatment primary breast carcinoma as well as multiple metastatic tumors and local breast recurrences obtained at autopsy, indicative of a distinct early subclone with the capability to resist multiple lines of treatment and eventually cause death. In addition, multiplex immunofluorescence revealed that tumor heterogeneity is significantly associated with the degree of infiltration of B lymphocytes in triple-negative breast cancer, a subtype with a large immune component. Collectively, these data reveal the functional potential of genetic subclones that comprise heterogeneous primary breast carcinomas and are selected for in CTCs and posttreatment breast cancer metastases. In addition, they uncover a relationship between tumor heterogeneity and host immune response in the tumor microenvironment. SIGNIFICANCE: As breast cancers progress, they become more heterogeneous for multiple regions amplified in circulating tumor cells, and intratumoral spatial heterogeneity is associated with the immune landscape.

Circulating tumor DNA is readily detectable among Ghanaian breast cancer patients supporting non-invasive cancer genomic studies in Africa.

Circulating tumor DNA (ctDNA) sequencing studies could provide novel insights into the molecular pathology of cancer in sub-Saharan Africa. In 15 patient plasma samples collected at the time of diagnosis as part of the Ghana Breast Health Study and unselected for tumor grade and subtype, ctDNA was detected in a majority of patients based on whole- genome sequencing at high (30×) and low (0.1×) depths. Breast cancer driver copy number alterations were observed in the majority of patients.

Comparative survival analysis of multiparametric tests-when molecular tests disagree-A TEAM Pathology study.

Multiparametric assays for risk stratification are widely used in the management of both node negative and node positive hormone receptor positive invasive breast cancer. Recent data from multiple sources suggests that different tests may provide different risk estimates at the individual patient level. The TEAM pathology study consists of 3284 postmenopausal ER+ve breast cancers treated with endocrine therapy Using genes comprising the following multi-parametric tests OncotypeDx®, Prosigna™ and MammaPrint® signatures were trained to recapitulate true assay results. Patients were then classified into risk groups and survival assessed. Whilst likelihood χ2 ratios suggested limited value for combining tests, Kaplan-Meier and LogRank tests within risk groups suggested combinations of tests provided statistically significant stratification of potential clinical value. Paradoxically whilst Prosigna-trained results stratified Oncotype-trained subgroups across low and intermediate risk categories, only intermediate risk Prosigna-trained cases were further stratified by Oncotype-trained results. Both Oncotype-trained and Prosigna-trained results further stratified MammaPrint-trained low risk cases, and MammaPrint-trained results also stratified Oncotype-trained low and intermediate risk groups but not Prosigna-trained results. Comparisons between existing multiparametric tests are challenging, and evidence on discordance between tests in risk stratification presents further dilemmas. Detailed analysis of the TEAM pathology study suggests a complex inter-relationship between test results in the same patient cohorts which requires careful evaluation regarding test utility. Further prognostic improvement appears both desirable and achievable.

Evaluation of multiple transcriptomic gene risk signatures in male breast cancer.

Male breast cancer (BCa) is a rare disease accounting for less than 1% of all breast cancers and 1% of all cancers in males. The clinical management is largely extrapolated from female BCa. Several multigene assays are increasingly used to guide clinical treatment decisions in female BCa, however, there are limited data on the utility of these tests in male BCa. Here we present the gene expression results of 381 M0, ER+ve, HER2-ve male BCa patients enrolled in the Part 1 (retrospective analysis) of the International Male Breast Cancer Program. Using a custom NanoString™ panel comprised of the genes from the commercial risk tests Prosigna®, OncotypeDX®, and MammaPrint®, risk scores and intrinsic subtyping data were generated to recapitulate the commercial tests as described by us previously. We also examined the prognostic value of other risk scores such as the Genomic Grade Index (GGI), IHC4-mRNA and our prognostic 95-gene signature. In this sample set of male BCa, we demonstrated prognostic utility on univariate analysis. Across all signatures, patients whose samples were identified as low-risk experienced better outcomes than intermediate-risk, with those classed as high risk experiencing the poorest outcomes. As seen with female BCa, the concordance between tests was poor, with C-index values ranging from 40.3% to 78.2% and Kappa values ranging from 0.17 to 0.58. To our knowledge, this is the largest study of male breast cancers assayed to generate risk scores of the current commercial and academic risk tests demonstrating comparable clinical utility to female BCa.

Assessment of Ki67 in Breast Cancer: Updated Recommendations From the International Ki67 in Breast Cancer Working Group.

Ki67 immunohistochemistry (IHC), commonly used as a proliferation marker in breast cancer, has limited value for treatment decisions due to questionable analytical validity. The International Ki67 in Breast Cancer Working Group (IKWG) consensus meeting, held in October 2019, assessed the current evidence for Ki67 IHC analytical validity and clinical utility in breast cancer, including the series of scoring studies the IKWG conducted on centrally stained tissues. Consensus observations and recommendations are: 1) as for estrogen receptor and HER2 testing, preanalytical handling considerations are critical; 2) a standardized visual scoring method has been established and is recommended for adoption; 3) participation in and evaluation of quality assurance and quality control programs is recommended to maintain analytical validity; and 4) the IKWG accepted that Ki67 IHC as a prognostic marker in breast cancer has clinical validity but concluded that clinical utility is evident only for prognosis estimation in anatomically favorable estrogen receptor-positive and HER2-negative patients to identify those who do not need adjuvant chemotherapy. In this T1-2, N0-1 patient group, the IKWG consensus is that Ki67 5% or less, or 30% or more, can be used to estimate prognosis. In conclusion, analytical validity of Ki67 IHC can be reached with careful attention to preanalytical issues and calibrated standardized visual scoring. Currently, clinical utility of Ki67 IHC in breast cancer care remains limited to prognosis assessment in stage I or II breast cancer. Further development of automated scoring might help to overcome some current limitations.