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Purpose:The limited knowledge of the molecular alterations that characterize poorly differentiated neuroendocrine carcinomas has limited the clinical development of targeted agents directed to driver mutations. Here we aim to identify new molecular targets in colon neuroendocrine carcinomas (co-NEC) and proof the efficacy of matching drugs.Experimental Design:We performed a multi-omic analysis of co-NEC to identify genetic or epigenetic alterations that could be exploited as effective drug targets. We compared co-NEC samples with colorectal carcinomas (CRC) to identify neuroendocrine-specific traits. Patients with co-NEC and patient-derived xenografts were treated with a BRAFV600E-blocking drug to demonstrate sensitivity.Results:co-NEC and CRC are similar in their mutational repertoire, although co-NECs are particularly enriched in BRAFV600E mutations. We report for the first time that V600EBRAF-mutant co-NECs may benefit from BRAF inhibition in monotherapy and how EGFR status is essential to predict innate sensitivity and acquired resistance by a differential methylation of its gene regulatory regions.Conclusions:The identification of V600E BRAF mutations in high-grade co-NECs has allowed the description of radiological responses to combination therapy of BRAF and MEK inhibitors in basket clinical trials. However, the molecular rationale for this treatment combination was based on the presence of the BRAF mutation and the efficacy observed in other cancer types such as melanoma. Future drug development in this setting should test BRAF inhibitors upfront and the addition of anti-EGFR antibodies instead of MEK inhibitors for an efficient blockade of acquired resistance.

Background: The potential gonadotoxicity of anti-HER2 agents remains largely unknown, and limited, conflicting evidence exists for taxanes. Antimüllerian hormone (AMH) is an established biomarker of ovarian reserve that may aid in quantifying anticancer treatment–induced gonadotoxicity. Patients and Methods: The present biomarker analysis of the randomized phase III neoadjuvant NeoALTTO trial included premenopausal women aged ≤45 years at diagnosis of HER2-positive early breast cancer with available frozen serum samples at baseline (ie, before anticancer treatments), at week 2 (ie, the “biological window” of anti-HER2 therapy alone), and/or at the time of surgery (ie, after completing paclitaxel + anti-HER2 therapy, before starting adjuvant chemotherapy). Results: The present analysis included 130 patients with a median age of 38 years (interquartile ratio [IQR], age 33–42 years). AMH values at the 3 time points differed significantly (P

Purpose: The limited knowledge of the molecular alterations that characterize poorly differentiated neuroendocrine carcinomas has limited the clinical development of targeted agents directed to driver mutations. Here we aim to identify new molecular targets in colon neuroendocrine carcinomas (co-NEC) and proof the efficacy of matching drugs. Experimental Design: We performed a multi-omic analysis of co-NEC to identify genetic or epigenetic alterations that could be exploited as effective drug targets. We compared co-NEC samples with colorectal carcinomas (CRC) to identify neuroendocrine-specific traits. Patients with co-NEC and patient-derived xenografts were treated with a BRAFV600E-blocking drug to demonstrate sensitivity. Results: co-NEC and CRC are similar in their mutational repertoire, although co-NECs are particularly enriched in BRAFV600E mutations. We report for the first time that V600EBRAF-mutant co-NECs may benefit from BRAF inhibition in monotherapy and how EGFR status is essential to predict innate sensitivity and acquired resistance by a differential methylation of its gene regulatory regions. Conclusions: The identification of V600E BRAF mutations in high-grade co-NECs has allowed the description of radiological responses to combination therapy of BRAF and MEK inhibitors in basket clinical trials. However, the molecular rationale for this treatment combination was based on the presence of the BRAF mutation and the efficacy observed in other cancer types such as melanoma. Future drug development in this setting should test BRAF inhibitors upfront and the addition of anti-EGFR antibodies instead of MEK inhibitors for an efficient blockade of acquired resistance.

Cancer; Cancer genetics Cáncer; Genética del cáncer Càncer; Genètica del càncer There is a growing need for systems that efficiently support the work of medical teams at the precision-oncology point of care. Here, we present the implementation of the Molecular Tumor Board Portal (MTBP), an academic clinical decision support system developed under the umbrella of Cancer Core Europe that creates a unified legal, scientific and technological platform to share and harness next-generation sequencing data. Automating the interpretation and reporting of sequencing results decrease the need for time-consuming manual procedures that are prone to errors. The adoption of an expert-agreed process to systematically link tumor molecular profiles with clinical actions promotes consistent decision-making and structured data capture across the connected centers. The use of information-rich patient reports with interactive content facilitates collaborative discussion of complex cases during virtual molecular tumor board meetings. Overall, streamlined digital systems like the MTBP are crucial to better address the challenges brought by precision oncology and accelerate the use of emerging biomarkers. Open access funding provided by Karolinska Institute

Long noncoding RNAs (lncRNAs) are regulatory molecules which have been traditionally considered as “non-coding”. Strikingly, recent evidence has demonstrated that many non-coding regions, including lncRNAs, do in fact contain small-open reading frames that code for small proteins that have been called microproteins. Only a few of them have been characterized so far, but they display key functions in a wide variety of cellular processes. Here, we show that TUNAR lncRNA encodes an evolutionarily conserved microprotein expressed in the nervous system that we have named pTUNAR. pTUNAR deficiency in mouse embryonic stem cells improves their differentiation potential towards neural lineage both in vitro and in vivo. Conversely, pTUNAR overexpression impairs neuronal differentiation by reduced neurite formation in different model systems. At the subcellular level, pTUNAR is a transmembrane protein that localizes in the endoplasmic reticulum and interacts with the calcium transporter SERCA2. pTUNAR overexpression reduces cytoplasmatic calcium, consistent with a possible role of pTUNAR as an activator of SERCA2. Altogether, our results suggest that our newly discovered microprotein has an important role in neural differentiation and neurite formation through the regulation of intracellular calcium. From a more general point of view, our results provide a proof of concept of the role of lncRNAs-encoded microproteins in neural differentiation., Work in the Abad lab is supported by VHIO, Fero Foundation, La Caixa Foundation (HR18-00256), Asociación Española Contra el Cancer (AECC), Cellex Foundation, Mutua Madrileña Foundation and by grants from the Spanish Ministry of Science and Innovation (SAF2015-69413-R; RTI2018-102046-B-I00). M.A. was recipient of a Ramon y Cajal contract from the Spanish Ministry of Science and Innovation (RYC-2013-14747). E.S. was recipient of a AECC Postdoctoral Fellowship. L.H-M. also acknowledges funding from grants SAF2017-88019-C3-1R y PID2020-116927RB-C21 from the Spanish Government. MG is supported by the advanced ERC grant NeuroCentro and the German Research Foundation (SFB870; SPP2202; SPP2306; SYNERGY; TRR274). DT is supported by the Ramón y Cajal program (RYC-2017-23486/RTI2018-095580-A-I00). MMA acknowledges funding from the Spanish Ministry of Science and Innovation PGC2018-094091-B-I00 co-funded by FEDER.

Purpose: The companion diagnostic test for trastuzumab has not changed much in the last 25 years. We used high-plex digital spatial profiling to identify biomarkers besides HER2 that can help predict response to trastuzumab in HER2-positive breast cancer. Experimental design: Fifty-eight protein targets were measured in three different molecularly defined compartments by the NanoString GeoMx Digital Spatial Profiler (DSP) in a tissue microarray containing 151 patients with breast cancer that received adjuvant trastuzumab as part of the Hellenic Cooperative Oncology Group 10/05 clinical trial. Promising candidate biomarkers were orthogonally validated with quantitative immunofluorescence (QIF). RNA-sequencing data from the Neoadjuvant Lapatinib and/or Trastuzumab Treatment Optimisation Study (NeoALTTO) were accessed to provide independent cohort validation. Disease-free survival (DFS) was the main outcome assessed. Statistical analyses were performed using a two-sided test (alpha = 0.05) and multiple testing correction (Benjamini-Hochberg method, FDR < 0.1). Results: By DSP, high expression of alpha-smooth muscle actin (alpha-SMA), both in the leukocyte and stromal compartments, was associated with shorter DFS in univariate analysis (P = 0.002 and P = 0.023, respectively). High alpha-SMA expression in the stroma was validated by QIF after controlling for estrogen receptor and progesterone receptor status [HR, 3.12; 95% confidence interval (CI), 1.12-8.68; P = 0.029] showing recurrence on trastuzumab in the same cohort. In the NeoALTTO cohort, elevated levels of ACTA2 were predictive for shorter DFS in the multivariate analysis (HR, 3.21; 95% CI, 1.14-9.05; P = 0.027). Conclusions: This work identifies a-SMA as a novel, easy-to-implement biomarker of resistance to trastuzumab that may be valuable in settings where trastuzumab is combined with other therapies.

BACKGROUND: Tumor infiltrating lymphocytes (TILs) are associated with benefit to trastuzumab and chemotherapy in early-stage HER2+ breast cancer (BC) patients. The predictive value of TILs, TIL subsets, and other immune cells in patients receiving chemotherapy-sparing lapatinib plus trastuzumab (LT) treatment is unclear. EXPERIMENTAL DESIGN: H&E-stained slides (n=59) were used to score stromal (s-)TILs from pre-treatment biopsies of patients enrolled in the neoadjuvant TBCRC006 trial of 12-week LT therapy (plus endocrine therapy for ER+ tumors). A 60% threshold was used to define lymphocyte-predominant BC (LPBC). Multiplexed immunofluorescence (m-IF) staining (CD4, CD8, CD20, CD68, and FoxP3) and multispectral imaging were performed to characterize immune infiltrates in single FFPE slides (n=33). RESULTS: The pathologic complete response (pCR) rate was numerically higher in LPBC patients compared to non-LPBC patients (50% vs. 19%, P=0.057). Unsupervised hierarchical clustering of the five immune markers identified two patient clusters with different responses to LT treatment (pCR = 7% vs. 50%, for Cluster 1 vs. 2 respectively, P=0.01). In multivariable analysis, Cluster 2, characterized by high CD4+, CD8+, CD20+ s-TILs, and high CD20+ intratumoral TILs, was independently associated with a higher pCR rate (P=0.03). Analysis of single immune subpopulations revealed a significant association of pCR with higher baseline infiltration by s-CD4, intratumoral (i-) CD4, and i-CD20+ TILs. CONCLUSIONS: LPBC was marginally associated with higher pCR rate than non-LPBC in LT treated HER2+ BC patients. Quantitative assessment of the immune infiltrate by m-IF is feasible and may help correlate individual immune cell subpopulations and immune cell profiles with treatment response.

Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring.

Purpose: The limited knowledge of the molecular alterations that characterize poorly differentiated neuroendocrine carcinomas has limited the clinical development of targeted agents directed to driver mutations. Here we aim to identify new molecular targets in colon neuroendocrine carcinomas (co-NEC) and proof the efficacy of matching drugs.Experimental Design: We performed a multiomic analysis of co-NEC to identify genetic or epigenetic alterations that could be exploited as effective drug targets. We compared co-NEC samples with colorectal carcinomas (CRC) to identify neuroendocrine specific traits. Patients with co-NEC and derived-xenografts (PDX) were treated with a BRAFV600E blocking drug to demonstrate sensitivity.Results: co-NEC and CRC are similar in their mutational repertoire, although co-NECs are particularly enriched in BRAFV600E mutations. We report for the first time that V600EBRAF mutant colon neuroendocrine carcinomas may benefit from BRAF inhibition in monotherapy and how EGFR status is essential to predict innate sensitivity and acquired resistance by a differential methylation of its gene regulatory regions.Conclusions: The identification of V600E BRAF mutations in high grade colon neuroendocrine carcinomas has allowed the description of radiological responses to combination therapy of BRAF and MEK inhibitors in basket clinical trials. However, the molecular rationale for this treatment combination was based on the presence of the BRAF mutation and the efficacy observed in other cancer types such as melanoma. Future drug development in this setting should test BRAF inhibitors upfront and the addition of anti-EGFR antibodies instead of MEK inhibitors for an efficient blockade of acquired resistance.

We molecularly characterized tumors from non‐small cell lung cancer patients, focusing on long‐term responders to immune checkpoint inhibitors and showed that these patients present high tumor mutation burden and low somatic copy number alteration burden. PD‐L1 expression was also enriched in these patients. Finally, we validated our findings by reanalyzing two public datasets., Immunotherapy has transformed advanced non‐small cell lung cancer (NSCLC) treatment strategies and has led to unprecedented long‐lasting responses in some patients. However, the molecular determinants driving these long‐term responses remain elusive. To address this issue, we performed an integrative analysis of genomic and transcriptomic features of long‐term immune checkpoint inhibitors (ICIs)‐associated responders. We assembled a cohort of 47 patients with NSCLC receiving ICIs that was enriched in long‐term responders [>18 months of progression‐free survival (PFS)]. We performed whole‐exome sequencing from tumor samples, estimated the tumor mutational burden (TMB), and inferred the somatic copy number alterations (SCNAs). We also obtained gene transcription data for a subset of patients using Nanostring, which we used to assess the tumor immune infiltration status and PD‐L1 expression. Our results indicate that there is an association between TMB and benefit to ICIs, which is driven by those patients with long‐term response. Additionally, high SCNAs burden is associated with poor response and negatively correlates with the presence of several immune cell types (B cells, natural killers, regulatory T cells or effector CD8 T cells). Also, CD274 (PD‐L1) expression is increased in patients with benefit, mainly in those with long‐term response. In our cohort, combined assessment of TMB and SCNAs burden enabled identification of long‐term responders (considering PFS and overall survival). Notably, the association between TMB, SCNAs burden, and PD‐L1 expression with the outcomes of ICIs treatment was validated in two public datasets of ICI‐treated patients with NSCLC. Thus, our data indicate that TMB is associated with long‐term benefit following ICIs treatment in NSCLC and that TMB, SCNAs burden, and PD‐L1 are complementary determinants of response to ICIs.

Background: Circulating tumor DNA (ctDNA) is a potential source for tumor genome analysis. We explored the concordance between the mutational status of RAS in tumor tissue and ctDNA in metastatic colorectal cancer (mCRC) patients to establish eligibility for anti-epidermal growth factor receptor (EGFR) therapy. Patients and methods: A prospective-retrospective cohort study was carried out. Tumor tissue from 146 mCRC patients was tested for RAS status with standard of care (SoC) PCR techniques, and Digital PCR (BEAMing) was used both in plasma and tumor tissue. Results: ctDNA BEAMing RAS testing showed 89.7% agreement with SoC (Kappa index 0.80; 95% CI 0.71 - 0.90) and BEAMing in tissue showed 90.9% agreement with SoC (Kappa index 0.83; 95% CI 0.74 - 0.92). Fifteen cases (10.3%) showed discordant tissue-plasma results. ctDNA analysis identified nine cases of low frequency RAS mutations that were not detected in tissue, possibly due to technical sensitivity or heterogeneity. In six cases, RAS mutations were not detected in plasma, potentially explained by low tumor burden or ctDNA shedding. Prediction of treatment benefit in patients receiving anti-EGFR plus irinotecan in second- or third-line was equivalent if tested with SoC PCR and ctDNA. Forty-eight percent of the patients showed mutant allele fractions in plasma below 1%. Conclusions: Plasma RAS determination showed high overall agreement and captured a mCRC population responsive to anti-EGFR therapy with the same predictive level as SoC tissue testing. The feasibility and practicality of ctDNA analysis may translate into an alternative tool for anti-EGFR treatment selection., This work was supported by Merck, S.L., Madrid, Spain, an affiliate of Merck KGaA, Darmstadt, Germany and partially by the Instituto de Salud Carlos III (Ministerio de Economia y Competitividad) and 'Fondo Europeo de Desarrollo Regional (FEDER), una manera de hacer Europa' grants [FIS PI12-01589 to RS] and RETICC Cancer: Grupo Cancer Digestivo - Instituto de Salud Carlos III. TTD ULTRA study (EC11-050) was supported by the Ministerio de Sanidad y Politica Social [SPI/2885/2011]. To CM grants [PI15/00457 and DTS15/00048].

The limited knowledge of the molecular alterations that characterize poorly differentiated neuroendocrine carcinomas has limited the clinical development of targeted agents directed to driver mutations. Here we aim to identify new molecular targets in colon neuroendocrine carcinomas (co-NEC) and proof the efficacy of matching drugs.We performed a multi-omic analysis of co-NEC to identify genetic or epigenetic alterations that could be exploited as effective drug targets. We compared co-NEC samples with colorectal carcinomas (CRC) to identify neuroendocrine-specific traits. Patients with co-NEC and patient-derived xenografts were treated with a BRAFV600E-blocking drug to demonstrate sensitivity.co-NEC and CRC are similar in their mutational repertoire, although co-NECs are particularly enriched inThe identification of

Purpose Transcriptomic profiling of colorectal cancer (CRC) has led to the identification\ud of four consensus molecular subtypes (CMS1 to 4) that have prognostic value in stage\ud II and III disease. More recently, the Colorectal Cancer Intrinsic Subtypes (CRIS) classification system has helped to define the biology specific to the epithelial component\ud of colorectal tumors; however, the clinical value of these classification systems in the\ud prediction of response to standard-of-care adjuvant chemotherapy remains unknown.\ud Patients and Methods Using samples from four European sites, we assembled a novel\ud cohort of patients with stage II and III CRC (n = 156 samples) and performed transcriptomic profiling and targeted sequencing and generated a tissue microarray to enable\ud integrated multiomics analyses. We also accessed data from two published cohorts of\ud patients with stage II and III CRC: GSE39582 and GSE14333 (n = 479 and n = 185 samples, respectively).\ud Results The epithelial-rich CMS2 subtype of CRC benefitted significantly from treatment with adjuvant chemotherapy in both stage II and III disease (P = .02 and P < .001,\ud respectively), whereas the CMS3 subtype significantly benefitted in stage III only (P = .001).\ud After CRIS substratification of CMS2, we observed that only the CRIS-C subtype significantly benefitted from treatment with adjuvant chemotherapy in stage II and III disease (P = .0081 and P < .001, respectively), whereas the CRIS-D subtype significantly\ud benefitted in stage III only (P = .0034). We also observed that CRIS-C patients with\ud low levels of CD8+\ud tumor-infiltrating lymphocytes were most at risk for relapse in both\ud stage II and III disease (log-rank P = .0031; hazard ratio, 12.18 [95% CI, 1.51 to 98.58]).\ud Conclusion Patient stratification using a combination of transcriptional subtyping and\ud CD8 immunohistochemistry analyses is capable of identifying patients with poor prognostic stage II and III disease who benefit from adjuvant standard-of-care chemotherapy.\ud These findings are particularly relevant for patients with stage II disease, where the\ud overall benefit of adjuvant chemotherapy is marginal.

RAF kinase inhibitors are clinically active in patients with BRAF (V600E) mutant melanoma. However, rarely do tumors regress completely, with the majority of responses being short-lived. This is partially mediated through the loss of negative feedback loops after MAPK inhibition and reactivation of upstream signaling. Here, we demonstrate that the deubiquitinating enzyme USP28 functions through a feedback loop to destabilize RAF family members. Loss of USP28 stabilizes BRAF enhancing downstream MAPK activation and promotes resistance to RAF inhibitor therapy in culture and in vivo models. Importantly, we demonstrate that USP28 is deleted in a proportion of melanoma patients and may act as a biomarker for response to BRAF inhibitor therapy in patients. Furthermore, we identify Rigosertib as a possible therapeutic strategy for USP28-depleted tumors. Our results show that loss of USP28 enhances MAPK activity through the stabilization of RAF family members and is a key factor in BRAF inhibitor resistance.

Introduction: Current methods to determine HER2 (human epidermal growth factor receptor 2) status are affected by reproducibility issues and do not reliably predict benefit from anti‐HER2 therapy. Quantitative measurement of HER2 may more accurately identify breast cancer (BC) patients who will respond to anti‐HER2 treatments. Methods: Using selected reaction monitoring mass spectrometry (SRM‐MS), we quantified HER2 protein levels in formalin‐fixed, paraffin‐embedded (FFPE) tissue samples that had been classified as HER2 0, 1+, 2+ or 3+ by immunohistochemistry (IHC). Receiver operator curve (ROC) analysis was conducted to obtain optimal HER2 protein expression thresholds predictive of HER2 status (by standard IHC or in situ hybridization [ISH]) and of survival benefit after anti‐HER2 therapy. Results: Absolute HER2 amol/μg levels were significantly correlated with both HER2 IHC and amplification status by ISH (p 2200 amol/μg were significantly associated with longer disease‐free survival (DFS) and overall survival (OS) in an adjuvant setting and with longer OS in a metastatic setting. Conclusion: Quantitative HER2 measurement by SRM‐MS is superior to IHC and ISH in predicting outcome after treatment with anti‐HER2 therapy., Highlights We quantified by mass spectrometry the levels of HER2 in HER2‐positive breast tumors.The tumors with the highest HER2 levels benefitted most from HER2 inhibition.HER2 protein levels were better predicting markers than gene amplification.Double minute amplification pattern was associated with low HER2 levels.

International audience; Assessment of tumor-infiltrating lymphocytes (TILs) in histopathologic specimens can provide important prognostic information in diverse solid tumor types, and may also be of value in predicting response to treatments. However, implementation as a routine clinical biomarker has not yet been achieved. As successful use of immune checkpoint inhibitors and other forms of immunotherapy become a clinical reality, the need for widely applicable, accessible, and reliable immunooncology biomarkers is clear. In part 1 of this review we briefly discuss the host immune response to tumors and different approaches to TIL assessment. We propose a standardized methodology to assess TILs in solid tumors on hematoxylin and eosin sections, in both primary and metastatic settings, based on the International Immuno-Oncology Biomarker Working Group guidelines for TIL assessment in invasive breast carcinoma. A review of the literature regarding the value of TIL assessment in different solid tumor types follows in part 2. The method we propose is reproducible, affordable, easily applied, and has demonstrated prognostic and predictive significance in invasive breast carcinoma. This standardized methodology may be used as a reference against which other methods are compared, and should be evaluated for clinical validity and utility. Standardization of TIL assessment will help to improve consistency and reproducibility in this field, enrich both the quality and quantity of comparable evidence, and help to thoroughly evaluate the utility of TILs assessment in this era of immunotherapy.

Introducción: La expresión desregulada y la actividad de los miembros de la familia HER es frecuente en el cáncer de mama (CM). Hasta el 25% de CM sobreexpresan HER2. Los altos niveles de este oncogén, casi invariablemente como consecuencia de la amplificación genómica, conllevan una enfermedad agresiva y es una importante diana terapéutica. Los anticuerpos monoclonales y las pequeñas moléculas inhibidoras de quinasa son las principales estrategias dirigidas contra HER2 en CM. Aunque el tratamiento con trastuzumab se asocia con importantes beneficios en términos de supervivencia, un número significativo de pacientes con CM HER2-positivo no se benefician de ella o se vuelven resistentes. Otros fármacos anti-HER2 (por ejemplo, lapatinib, pertuzumab y T-DM1) han sido aprobados para el tratamiento de CM metastásico HER2-positivo después de la progresión a trastuzumab. Estos nuevos fármacos anti-HER2 están siendo probados en el tratamiento adyuvante, solo o en regímenes de anticuerpos duales sin quimioterapia concomitante o secuencial. Identificar qué pacientes con CM tienen más probabilidades de beneficiarse de una u otra forma de terapia dirigida anti-HER es crucial. Los métodos actuales para la determinación del estado de HER2 (IHC y FISH) son semicuantitativos, sufren de problemas de reproducibilidad, y no predicen la respuesta al trastuzumab. El objetivo principal de este proyecto fue investigar si el análisis cuantitativo de la proteína HER2 por espectrometría de masas (MS) puede mejorar la predicción actual de respuesta o resistencia a los medicamentos dirigidos contra HER. Métodos: Hemos cuantificado mediante MS los niveles de proteína HER2 en muestras de tejido, fijados en formol e incluidos en parafina que habían sido clasificadas como negativas (HER2 0, 1+), equívoca (2+) o positiva (3+) por inmunohistoquímica (IHC). Las curvas ROC (Característica Operativa del Receptor) se construyeron mediante el cálculo de la sensibilidad y especificidad de cantidades crecientes de HER2 (por MS) en la predicción de positividad de HER2 (por IHC/ISH combinado) y de beneficio en la supervivencia después de tratamiento con anti-HER2. El análisis de supervivencia se llevo a cabo con el método de Kaplan-Meier y las curvas se compararon mediante el test del Log-Rank. Para el análisis multivariable se utilizó la regresión de Cox ajustado por el estado de los receptores hormonales, el estadío del tumor, los ganglios linfáticos y los niveles de HER2 por MS. Los resultados se consideraron significativos cuando los valores de p (p) fueron menos de 0,05. Resultados: Los niveles absolutos de HER2 (amol/μg) se correlacionaron significativamente con HER2 por IHC y el estado de la amplificación por ISH (p 2200 mg amol/μg obtienen un beneficio más grande tras el tratamiento con la terapia anti-HER2 que los pacientes con bajos niveles de expresión de HER2., Introduction: Dysregulated expression and activity of HER family members is frequent in breast cancer (BC). Up to 25% of BC overexpress HER2. High levels of this oncogene, almost invariably as a consequence of genomic amplification, drives aggressive disease and is an important therapeutic target. Monoclonal antibodies and small molecules kinase inhibitors are the main strategies to target HER2 in BC. Although trastuzumab treatment is associated with considerable benefits in terms survival outcomes, a significant number of patients with HER2-positive BC do not benefit from it or become resistant. Other HER2-targeted drugs (eg, lapatinib, pertuzumab, and T-DM1) have been approved for the treatment of HER2-positive metastatic BC after progression on trastuzumab. These new HER2-targeted drugs are now being tested in the adjuvant setting, alone or in dual antibody regimens without concomitant or sequential chemotherapy. Identifying which patients with BC are most likely to benefit from one or another form of anti-HER targeted therapy is crucial. Current standard methods for the determination of HER2 status (IHC and FISH) are semiquantitative, suffers from reproducibility issues, and do not predict response to trastuzumab. In the present study we sought to investigate if quantitative analysis of HER2 by mass spectrometry (MS) may improve current prediction of response or resistance to HER-targeting drugs. Methods: Using selected reaction monitoring MS, we quantified HER2 protein levels in formalin-fixed, paraffin-embedded tissue samples that had been classified as negative (HER2 0, 1+), equivocal (2+) or positive (3+) by immunohistochemistry (IHC). Receiver operating characteristic (ROC) curves were constructed by computing the sensitivity and specificity of increasing quantities of HER2 (by MS) in predicting HER2 positivity (by combined IHC/ISH) and of survival benefit after anti- HER2 therapy. Survival was modeled using the Kaplan-Meier curves and the p-value obtained by the log-rank test. Multivariate survival analysis was performed using the Cox proportional hazards model adjusted for hormone receptor status, tumor stage, lymph node status and HER2 SRM levels. Results were considered significant when p-values (p) were less than 0.05. Results: Absolute HER2 amol/μg levels were significantly correlated with both HER2 IHC and amplification status by ISH (p2200 amol/mg benefit more from anti-HER2 therapy than patients with lower HER2 expression levels.

A chromosomal region that includes the gene encoding HER2, a receptor tyrosine kinase (RTK), is amplified in 20% of breast cancers. Although these tumors tend to respond to drugs directed against HER2, they frequently become resistant and resume their malignant progression. Gene amplification in double minutes (DMs), which are extrachromosomal entities whose number can be dynamically regulated, has been suggested to facilitate the acquisition of resistance to therapies targeting RTKs. Here we show that ~30% of HER2-positive tumors show amplification in DMs. However, these tumors respond to trastuzumab in a similar fashion than those with amplification of the HER2 gene within chromosomes. Furthermore, in different models of resistance to anti-HER2 therapies, the number of DMs containing HER2 is maintained, even when the acquisition of resistance is concomitant with loss of HER2 protein expression. Thus, both clinical and preclinical data show that, despite expectations, loss of HER2 protein expression due to loss of DMs containing HER2 is not a likely mechanism of resistance to anti-HER2 therapies.

Poly(ADP-ribose) polymerase (PARP) inhibitors (PARPi) are effective in cancers with defective homologous recombination DNA repair (HRR), including BRCA1/2-related cancers. A test to identify additional HRR-deficient tumors will help to extend their use in new indications. We evaluated the activity of the PARPi olaparib in patient-derived tumor xenografts (PDXs) from breast cancer (BC) patients and investigated mechanisms of sensitivity through exome sequencing, BRCA1 promoter methylation analysis, and immunostaining of HRR proteins, including RAD51 nuclear foci. In an independent BC PDX panel, the predictive capacity of the RAD51 score and the homologous recombination deficiency (HRD) score were compared. To examine the clinical feasibility of the RAD51 assay, we scored archival breast tumor samples, including PALB2-related hereditary cancers. The RAD51 score was highly discriminative of PARPi sensitivity versus PARPi resistance in BC PDXs and outperformed the genomic test. In clinical samples, all PALB2-related tumors were classified as HRR-deficient by the RAD51 score. The functional biomarker RAD51 enables the identification of PARPi-sensitive BC and broadens the population who may benefit from this therapy beyond BRCA1/2-related cancers.

Funder: U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI), Funder: National Center for Research Resources under award number 1 C06 RR12463-01, VA Merit Review Award IBX004121A from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service, the DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558), the DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440), the DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329), the Ohio Third Frontier Technology Validation Fund, the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University., Funder: Susan G Komen Foundation (CCR CCR18547966) and a Young Investigator Grant from the Breast Cancer Alliance., Funder: The Canadian Cancer Society, Funder: Breast Cancer Research Foundation (BCRF), Grant No. 17-194, Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring.

Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls.

Funder: Breast Cancer Research Foundation (BCRF); doi: https://doi.org/10.13039/100001006, Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting.

CDK4/6 inhibitors combined with endocrine therapy have demonstrated higher antitumor activity than endocrine therapy alone for the treatment of advanced estrogen receptor-positive breast cancer. Some of these tumors are de novo resistant to CDK4/6 inhibitors and others develop acquired resistance. Here, we show that p16 overexpression is associated with reduced antitumor activity of CDK4/6 inhibitors in patient-derived xenografts (n = 37) and estrogen receptor-positive breast cancer cell lines, as well as reduced response of early and advanced breast cancer patients to CDK4/6 inhibitors (n = 89). We also identified heterozygous RB1 loss as biomarker of acquired resistance and poor clinical outcome. Combination of the CDK4/6 inhibitor ribociclib with the PI3K inhibitor alpelisib showed antitumor activity in estrogen receptor-positive non-basal-like breast cancer patient-derived xenografts, independently of PIK3CA, ESR1 or RB1 mutation, also in drug de-escalation experiments or omitting endocrine therapy. Our results offer insights into predicting primary/acquired resistance to CDK4/6 inhibitors and post-progression therapeutic strategies. This study has been supported by the Susan G. Komen Foundation (CCR15330331) and by the Catalan Agency AGAUR (2017 SGR 540) [to V.S.]. V.S. received funds from the Instituto de Salud Carlos III: grants PI13/01714, CP14/00228, MV15/00041, CPII19/00033 and PI20/00892. M.P. received a Juan de la Cierva Grant from the Ministerio de Economía y Competitividad (FJCI-2015-25412), L.Mo. a grant from FI-AGAUR (2019 FI_B 01199), F.B-M. a grant from the Fundación Científica Asociación Española Contra el Cáncer (AECC_Postdoctoral17-1062) and M.S-G, a Marie Slodowska-Curie Innovative Training Networks PhD fellowship (H2020-MSCA-ITN-2015_675392). This work was supported by Breast Cancer Research Foundation (BCRF-19-08), Instituto de Salud Carlos III Project Reference number AC15/00062 and the EC under the framework of the ERA-NET TRANSCAN-2 initiative co-financed by FEDER, Instituto de Salud Carlos III (CB16/12/00449 and PI19/01181) and Asociación Española Contra el Cáncer (to J.A.). R.B.C. laboratory is supported by Breast Cancer Now (grant numbers: MAN-Q1 and MAN-Q2), NIHR Manchester Biomedical Research Centre (IS-BRC-1215-20007) and EdiREX Horizon 2020 grant No.731105. The xenograft program in the C.C. laboratory is supported by Cancer Research UK and also received funding from an EU H2020 Network of Excellence (EuroCAN). This work has been supported by NIH grants P30 CA008748 and RO1CA190642-01, the CDMRP grant BC171535P1, and the Breast Cancer Research Foundation [to M.S.]. A.P. received funds from Instituto de Salud Carlos III—PI16/00904 and PI19/01846, Breast Cancer Now—2018NOVPCC1294, Breast Cancer Research Foundation-AACR Career Development Awards for Translational Breast Cancer Research 19-20-26-PRAT, Fundació La Marató TV3 201935-30, the European Union’s Horizon 2020 research and innovation program H2020-SC1-BHC-2018-2020. IRB Barcelona is a recipient of a Severo Ochoa Centre of Excellence Award from the Spanish Ministry of Economy and Competitiveness (MINECO; Government of Spain) and is supported by CERCA (Generalitat de Catalunya). C. S. Verma reports grants from MSD International and grants from Ipsen outside the submitted work.

Introducció. La medicina personalitzada promet el diagnòstic i el tractament de malalties a nivell individual i depèn en gran manera de la qualitat de les mostres clíniques i els assajos de diagnòstic. A mesura que es disposa d'opcions de tractament més específiques, es requereixen proves per a múltiples marcadors tumorals i es necessita optimitzar l'ús de mostres per a permetre un flux de treball de diagnòstic complet. A més, la caracterització de l'estat immunitari dels pacients es torna cada vegada més important per a la inmunooncología. L'extracció d'informació i els coneixements biològics requerits a partir de portaobjectes de teixit continua sent un desafiament amb els mètodes tradicionals basats ​​en teixits. Les dades de recerques recents han demostrat que els cicles iteratius de tinció i descoloració es poden realitzar en un sol portaobjectes de teixit sense perdre antigenicitat. No obstant això, la metodologia proposada era manual, laboriosa i lenta, la qual cosa limitava la seva aplicabilitat fora d'un entorn de recerca. Objectius. Planegem desenvolupar i validar panells de NGI específics compostos per diferents biomarcadors dissenyats per a abordar a) la quantificació del biomarcador KI67 en cèl·lules tumorals de manera reproduïble i automatitzada; b) la caracterització del microambient tumoral; i c) la caracterització dels fenotips de les cèl·lules tumorals de càncer de mama, heterogeneïtat i interaccions espacials amb cèl·lules T citotòxiques. Resultats. En el primer estudi es va dissenyar un panell NGI compost per KI67 per a la informació de proliferació i PanCK per a reconeixement de cèl·lules tumorals; el que ens va permetre, juntament amb l'anàlisi d'imatges, quantificar el KI67 en les cèl·lules tumorals de manera automàtica i solucionar els problemes de reproducibilitat que té la cuantificació del KI67. En el segon estudi es va dissenyar un panell compost per diferents biomarcadors per a explorar les cèl·lules T: CD3 (cèl·lules T), Foxp3 (cèl·lules T reguladores), CD4 (cèl·lules T auxiliars), CD8 (cèl·lules T citotòxiques), KI67 (marcador de proliferació), PanCK (reconeixement de células tumorals) que ens va permetre quantificar els diferents subtipus de cèl·lules T en la mostra, la seva distribució espacial i la seva anàlisi de proliferació. En el tercer estudi, un panell compost per KI67, receptor d'estrogen (ER), receptor de progesterona (PR), HER2 (receptor 2 del factor de creixement epidèrmic humà) i PanCK va proporcionar informació sobre l'expressió de cada biomarcador a nivell cel·lular; el que va permetre l'anàlisi de coexpresió en la mateixa cèl·lula, la seva distribució, la seva interacció espacial (cèl·lula tumoral-cèl·lula tumoral, cèl·lula tumoral-cèl·lules immunes) i els seus canvis durant el tractament anti-Her2. Conclusions. NGI ha estat desenvolupat, validat i utilitzat en diferents estudis. Pot ser utilitzat en qualsevol laboratori de patologia o recerca que estigui equipat per a patologia digital, d'una forma relativament senzilla i econòmica. Utilitza un únic portaobjectes per a cadascun dels panells, estalviant material per a anàlisis posteriors. NGI proporciona resultats reproduïbles que són comparables als IHC estàndard. NGI quantifica diferents biomarcadors a nivell d'una sola cèl·lula, proporcionant anàlisis de coexpresión i espacials; informació que ajuda a comprendre millor la biologia i la complexitat del tumor. Aquesta informació podria usar-se per a la predicció de la resposta a tractaments i per a identificar nous o millors biomarcadors per a predir la resposta al tractament i recolzar una millor estratificació dels pacients cap a diferents immunoteràpies o combinacions de teràpies. Introducción. La medicina personalizada promete el diagnóstico y el tratamiento de enfermedades a nivel individual y depende en gran medida de la calidad de las muestras clínicas y los ensayos de diagnóstico. A medida que se dispone de opciones de tratamiento más específicas, se requieren pruebas para múltiples marcadores tumorales y se necesita optimizar el uso de muestras para permitir un flujo de trabajo de diagnóstico completo. Además, la caracterización del estado inmunitario de los pacientes se vuelve cada vez más importante para la inmunooncología. La extracción de información y los conocimientos biológicos requeridos a partir de portaobjetos de tejido sigue siendo un desafío con los métodos tradicionales basados ​​en tejidos. Los datos de investigaciones recientes han demostrado que los ciclos iterativos de tinción y decoloración se pueden realizar en un solo portaobjetos de tejido sin perder antigenicidad. Sin embargo, la metodología propuesta era manual, laboriosa y lenta, lo que limitaba su aplicabilidad fuera de un entorno de investigación. Objetivos. Planeamos desarrollar y validar paneles de NGI específicos compuestos por diferentes biomarcadores diseñados para abordar a) la cuantificación del biomarcador KI67 en células tumorales de forma reproducible y automatizada; b) la caracterización del microambiente tumoral; y c) la caracterización de los fenotipos de las células tumorales de cáncer de mama, heterogeneidad e interacciones espaciales con células T citotóxicas. Resultados. En el primer estudio se diseñó un panel NGI compuesto por KI67 para la información de proliferación y PanCK para reconocimiento de células tumorales; lo que nos permitió, junto con el análisis de imágenes, cuantificar el KI67 en las células tumorales de forma automática y solucionar los problemas de reproducibilidad que tiene la cuantificación del KI67. En el segundo estudio se diseñó un panel compuesto por diferentes biomarcadores para explorar las células T: CD3 (células T), Foxp3 (células T reguladoras), CD4 (células T auxiliares), CD8 (células T citotóxicas), KI67 (marcador de proliferación), PanCK (reconocimiento de células tumorales) que nos permitió cuantificar los diferentes subtipos de células T en la muestra, su distribución espacial y su análisis de proliferación. En el tercer estudio, un panel compuesto por KI67, receptor de estrógeno (ER), receptor de progesterona (PR), HER2 (receptor 2 del factor de crecimiento epidérmico humano) y PanCK proporcionó información sobre la expresión de cada biomarcador a nivel celular; lo que permitió el análisis de coexpresión en la misma célula, su distribución, su interacción espacial (célula tumoral-célula tumoral, célula tumoral-células inmunes) y sus cambios durante el tratamiento anti-Her2. Conclusiones. NGI ha sido desarrollado, validado y utilizado en diferentes estudios. Puede ser utilizado en cualquier laboratorio de patología o investigación que esté equipado para patología digital, de una forma relativamente sencilla y económica. Utiliza un único portaobjetos para cada uno de los paneles, ahorrando material para análisis posteriores. NGI proporciona resultados reproducibles que son comparables a los IHC estándar. NGI cuantifica diferentes biomarcadores a nivel de una sola célula, proporcionando análisis de coexpresión y espaciales; información que ayuda a comprender mejor la biología y la complejidad del tumor. Esta información podría usarse para la predicción de la respuesta a tratamientos y para identificar nuevos o mejores biomarcadores para predecir la respuesta al tratamiento y respaldar una mejor estratificación de los pacientes hacia diferentes inmunoterapias o combinaciones de terapias. Introduction. Personalized medicine promises diagnosis and treatment of disease at the individual level and relies heavily on clinical specimen and diagnostic assay quality. As more targeted treatment options become available, testing for multiple tumor markers is required and optimization of sample use is needed to allow for a complete diagnostic workflow. In addition, characterization of the immune status of patients becomes increasingly important to immuno-oncology. The required extraction of information and biological insights from tissue slides remains challenging using traditional tissue-based methods. Recent research data have shown that iterative cycles of staining and destaining can be performed in a single tissue slide without losing antigenicity. However, the methodology proposed was manual, labor-intensive and time-consuming, thus limiting its applicability outside a research environment. Hypothesis. We have developed an innovative, simple, robust and automatized methodology, Next Generation Immunohistochemistry (NGI), to sequentially determine the expression of multiple individual biomarkers in a single tissue section. NGI may fill the actual limitations of the current approaches and become one of the multiplexed imaging technologies that could be used in different pathology and research laboratories to improve biomarker analyses in precision oncology. NGI may allow for a comprehensive characterization of biological tissue samples at cellular level while maintaining important spatial distribution/interaction between tumor and its microenvironment, information necessary to understand tumor biology and complexity. Objectives. We plan to develop and validate specific NGI panels composed of different biomarkers designed to address the a) quantification of KI67 biomarker in tumor cells in a reproducible and automated way; b) characterization of the tumor microenvironment; and c) characterization of breast cancer tumor cell phenotypes, heterogeneity and spatial interactions with cytotoxic t-cells. Results. In the first study, an NGI panel composed of KI67 for proliferation information and PanCK for tumor cell recognition was designed, which allowed us together with image analysis, to quantify KI67 in the tumor cells automatically and solve the reproducibility issues that KI67 index has. In the second study a panel composed of different biomarkers to explore the t-cells was designed: CD3 (t-cells), Foxp3 (regulatory t-cells), CD4 (helper t-cells), CD8 (cytotoxic t-cells), KI67 (proliferation marker), PanCK (tumor recognition) that allowed us the quantification of the different t-cell subtypes in the sample, their spatial distribution and their proliferation analyses. In the third study a panel composed of KI67, estrogen receptor (ER), progesteron receptor (PR), HER2 (human epidermal growth factor receptor-2) and PanCK provided information on the expression of each biomarker at a single-cell level, allowing analysis of their co-expression in the same cell, their distribution, their spatial interaction (tumor cell-tumor cell, tumor cell-immune cells) and their changes during anti-Her2 treatment. Conclusions. NGI has been developed, validated and used in different studies. It can be used in any pathology or research laboratory that is equipped for digital pathology, in a relatively simple and inexpensive way. It only uses a single slide for each of the panels saving material for further analyses. NGI provides reproducible results that are comparable to standard IHCs. NGI quantifies different biomarkers at a single cell level, providing co-expression and spatial analyses, information that helps deeper understand the tumor biology and complexity; information that could be used for response prediction and for identifying better or new biomarkers to predict response to treatment and supporting better patient stratification towards different immunotherapies or therapy combinations.

Biomarkers; Colorectal cancer; Immunotherapy Biomarcadors; Càncer colorectal; Immunoteràpia Biomarcadores; Cáncer colorrectal; Inmunoterapia The search for immunotherapy biomarkers in Microsatellite Instability High/Deficient Mismatch Repair system (MSI-H/dMMR) metastatic colorectal cancer (mCRC) is an unmet need. Sixteen patients with mCRC and MSI-H/dMMR (determined by either immunohistochemistry or polymerase chain reaction) treated with PD-1/PD-L1 inhibitors at our institution were included. According to whether the progression-free survival with PD-1/PD-L1 inhibitors was longer than 6 months or shorter, patients were clustered into the IT-responder group (n: 9 patients) or IT-resistant group (n: 7 patients), respectively. In order to evaluate determinants of benefit with PD-1/PD-L1 inhibitors, we performed multimodal analysis including genomics (through NGS panel tumour-only with 431 genes) and the immune microenvironment (using CD3, CD8, FOXP3 and PD-L1 antibodies). The following mutations were more frequent in IT-resistant compared with IT-responder groups: B2M (4/7 versus 2/9), CTNNB1 (2/7 versus 0/9), and biallelic PTEN (3/7 versus 1/9). Biallelic ARID1A mutations were found exclusively in the IT-responder group (4/9 patients). Tumour mutational burden did not correlate with immunotherapy benefit, neither the rate of indels in homopolymeric regions. Of note, biallelic ARID1A mutated tumours had the highest immune infiltration and PD-L1 scores, contrary to tumours with CTNNB1 mutation. Immune microenvironment analysis showed higher densities of different T cell subpopulations and PD-L1 expression in IT-responders. Misdiagnosis of MSI-H/dMMR inferred by discordances between immunohistochemistry and polymerase chain reaction was only found in the IT-resistant population (3/7 patients). Biallelic ARID1A mutations and Wnt signalling activation through CTNNB1 mutation were associated with high and low T cell immune infiltrates, respectively, and deserve special attention as determinants of response to PD-1/PD-L1 inhibitors. The non-MSI-H phenotype in dMMR is associated with poor benefit to immunotherapy. Our results suggest that mechanisms of resistance to immunotherapy are multi-factorial. This research was funded by Merck Research Grants (Call 2018) in the Area of Colorectal Cancer Clinical Investigation.

PARP inhibitors (PARPi) are approved drugs for platinum-sensitive, high-grade serous ovarian cancer (HGSOC) and for breast, prostate, and pancreatic cancers (PaC) harboring genetic alterations impairing homologous recombination repair (HRR). Detection of nuclear RAD51 foci in tumor cells is a marker of HRR functionality, and we previously established a test to detect RAD51 nuclear foci. Here, we aimed to validate the RAD51 score cut off and compare the performance of this test to other HRR deficiency (HRD) detection methods. Laboratory models from BRCA1/BRCA2-associated breast cancer, HGSOC, and PaC were developed and evaluated for their response to PARPi and cisplatin. HRD in these models and patient samples was evaluated by DNA sequencing of HRR genes, genomic HRD tests, and RAD51 foci detection. We established patient-derived xenograft models from breast cancer (n = 103), HGSOC (n = 4), and PaC (n = 2) that recapitulated patient HRD status and treatment response. The RAD51 test showed higher accuracy than HRR gene mutations and genomic HRD analysis for predicting PARPi response (95%, 67%, and 71%, respectively). RAD51 detection captured dynamic changes in HRR status upon acquisition of PARPi resistance. The accuracy of the RAD51 test was similar to HRR gene mutations for predicting platinum response. The predefined RAD51 score cut off was validated, and the high predictive value of the RAD51 test in preclinical models was confirmed. These results collectively support pursuing clinical assessment of the RAD51 test in patient samples from randomized trials testing PARPi or platinum-based therapies. Significance: This work demonstrates the high accuracy of a histopathology-based test based on the detection of RAD51 nuclear foci in predicting response to PARPi and cisplatin.

Background Identification of HER2-positive breast cancers with high anti-HER2 sensitivity could help de-escalate chemotherapy. Here, we tested a clinically applicable RNA-based assay that combines ERBB2 and the HER2-enriched (HER2-E) intrinsic subtype in HER2-positive disease treated with dual HER2-blockade without chemotherapy. Methods A research-based PAM50 assay was applied in 422 HER2-positive tumors from five II–III clinical trials (SOLTI-PAMELA, TBCRC023, TBCRC006, PER-ELISA, EGF104090). In SOLTI-PAMELA, TBCRC023, TBCRC006, and PER-ELISA, all patients had early disease and were treated with neoadjuvant lapatinib or pertuzumab plus trastuzumab for 12–24 weeks. Primary outcome was pathological complete response (pCR). In EGF104900, 296 women with advanced disease were randomized to receive either lapatinib alone or lapatinib plus trastuzumab. Progression-free survival (PFS), overall response rate (ORR), and overall survival (OS) were evaluated. Results A total of 305 patients with early and 117 patients with advanced HER2-positive disease were analyzed. In early disease, HER2-E represented 83.8% and 44.7% of ERBB2-high and ERBB2-low tumors, respectively. Following lapatinib and trastuzumab, the HER2-E and ERBB2 (HER2-E/ERBB2)-high group showed a higher pCR rate compared to the rest (44.5%, 95% confidence interval [CI] = 35.4% to 53.9% vs 11.6%, 95% CI = 6.9% to 18.0%; adjusted odds ratio [OR] = 6.05, 95% CI = 3.10 to 11.80, P Conclusions Combining HER2-E subtype and ERBB2 mRNA into a single assay identifies tumors with high responsiveness to HER2-targeted therapy. This biomarker could help de-escalate chemotherapy in approximately 40% of patients with HER2-positive breast cancer.