LOXL2-mediated chromatin compaction is required to maintain the oncogenic properties of triple-negative breast cancer cells.

Oxidation of histone H3 at lysine 4 (H3K4ox) is catalyzed by lysyl oxidase homolog 2 (LOXL2). This histone modification is enriched in heterochromatin in triple-negative breast cancer (TNBC) cells and has been linked to the maintenance of compacted chromatin. However, the molecular mechanism underlying this maintenance is still unknown. Here, we show that LOXL2 interacts with RuvB-Like 1 (RUVBL1), RuvB-Like 2 (RUVBL2), Actin-like protein 6A (ACTL6A), and DNA methyltransferase 1associated protein 1 (DMAP1), a complex involved in the incorporation of the histone variant H2A.Z. Our experiments indicate that this interaction and the active form of RUVBL2 are required to maintain LOXL2-dependent chromatin compaction. Genome-wide experiments showed that H2A.Z, RUVBL2, and H3K4ox colocalize in heterochromatin regions. In the absence of LOXL2 or RUVBL2, global levels of the heterochromatin histone mark H3K9me3 were strongly reduced, and the ATAC-seq signal in the H3K9me3 regions was increased. Finally, we observed that the interplay between these series of events is required to maintain H3K4ox-enriched heterochromatin regions, which in turn is key for maintaining the oncogenic properties of the TNBC cell line tested (MDA-MB-231).

A whirl of radiomics-based biomarkers in cancer immunotherapy, why is large scale validation still lacking?

The search for understanding immunotherapy response has sparked interest in diverse areas of oncology, with artificial intelligence (AI) and radiomics emerging as promising tools, capable of gathering large amounts of information to identify suitable patients for treatment. The application of AI in radiology has grown, driven by the hypothesis that radiology images capture tumor phenotypes and thus could provide valuable insights into immunotherapy response likelihood. However, despite the rapid growth of studies, no algorithms in the field have reached clinical implementation, mainly due to the lack of standardized methods, hampering study comparisons and reproducibility across different datasets. In this review, we performed a comprehensive assessment of published data to identify sources of variability in radiomics study design that hinder the comparison of the different model performance and, therefore, clinical implementation. Subsequently, we conducted a use-case meta-analysis using homogenous studies to assess the overall performance of radiomics in estimating programmed death-ligand 1 (PD-L1) expression. Our findings indicate that, despite numerous attempts to predict immunotherapy response, only a limited number of studies share comparable methodologies and report sufficient data about cohorts and methods to be suitable for meta-analysis. Nevertheless, although only a few studies meet these criteria, their promising results underscore the importance of ongoing standardization and benchmarking efforts. This review highlights the importance of uniformity in study design and reporting. Such standardization is crucial to enable meaningful comparisons and demonstrate the validity of biomarkers across diverse populations, facilitating their implementation into the immunotherapy patient selection process.

Identification of Precise 3D CT Radiomics for Habitat Computation by Machine Learning in Cancer.

Purpose To identify precise three-dimensional radiomics features in CT images that enable computation of stable and biologically meaningful habitats with machine learning for cancer heterogeneity assessment. Materials and Methods This retrospective study included 2436 liver or lung lesions from 605 CT scans (November 2010-December 2021) in 331 patients with cancer (mean age, 64.5 years ± 10.1 [SD]; 185 male patients). Three-dimensional radiomics were computed from original and perturbed (simulated retest) images with different combinations of feature computation kernel radius and bin size. The lower 95% confidence limit (LCL) of the intraclass correlation coefficient (ICC) was used to measure repeatability and reproducibility. Precise features were identified by combining repeatability and reproducibility results (LCL of ICC ≥ 0.50). Habitats were obtained with Gaussian mixture models in original and perturbed data using precise radiomics features and compared with habitats obtained using all features. The Dice similarity coefficient (DSC) was used to assess habitat stability. Biologic correlates of CT habitats were explored in a case study, with a cohort of 13 patients with CT, multiparametric MRI, and tumor biopsies. Results Three-dimensional radiomics showed poor repeatability (LCL of ICC: median [IQR], 0.442 [0.312-0.516]) and poor reproducibility against kernel radius (LCL of ICC: median [IQR], 0.440 [0.33-0.526]) but excellent reproducibility against bin size (LCL of ICC: median [IQR], 0.929 [0.853-0.988]). Twenty-six radiomics features were precise, differing in lung and liver lesions. Habitats obtained with precise features (DSC: median [IQR], 0.601 [0.494-0.712] and 0.651 [0.52-0.784] for lung and liver lesions, respectively) were more stable than those obtained with all features (DSC: median [IQR], 0.532 [0.424-0.637] and 0.587 [0.465-0.703] for lung and liver lesions, respectively; P < .001). In the case study, CT habitats correlated quantitatively and qualitatively with heterogeneity observed in multiparametric MRI habitats and histology. Conclusion Precise three-dimensional radiomics features were identified on CT images that enabled tumor heterogeneity assessment through stable tumor habitat computation. Keywords: CT, Diffusion-weighted Imaging, Dynamic Contrast-enhanced MRI, MRI, Radiomics, Unsupervised Learning, Oncology, Liver, Lung Supplemental material is available for this article. © RSNA, 2024 See also the commentary by Sagreiya in this issue.

Weakly Supervised Deep Learning Predicts Immunotherapy Response in Solid Tumors Based on PD-L1 Expression.

Programmed death-ligand 1 (PD-L1) IHC is the most commonly used biomarker for immunotherapy response. However, quantification of PD-L1 status in pathology slides is challenging. Neither manual quantification nor a computer-based mimicking of manual readouts is perfectly reproducible, and the predictive performance of both approaches regarding immunotherapy response is limited. In this study, we developed a deep learning (DL) method to predict PD-L1 status directly from raw IHC image data, without explicit intermediary steps such as cell detection or pigment quantification. We trained the weakly supervised model on PD-L1-stained slides from the non-small cell lung cancer (NSCLC)-Memorial Sloan Kettering (MSK) cohort (N = 233) and validated it on the pan-cancer-Vall d'Hebron Institute of Oncology (VHIO) cohort (N = 108). We also investigated the performance of the model to predict response to immune checkpoint inhibitors (ICI) in terms of progression-free survival. In the pan-cancer-VHIO cohort, the performance was compared with tumor proportion score (TPS) and combined positive score (CPS). The DL model showed good performance in predicting PD-L1 expression (TPS ≥ 1%) in both NSCLC-MSK and pan-cancer-VHIO cohort (AUC 0.88 ± 0.06 and 0.80 ± 0.03, respectively). The predicted PD-L1 status showed an improved association with response to ICIs [HR: 1.5 (95% confidence interval: 1-2.3), P = 0.049] compared with TPS [HR: 1.4 (0.96-2.2), P = 0.082] and CPS [HR: 1.2 (0.79-1.9), P = 0.386]. Notably, our explainability analysis showed that the model does not just look at the amount of brown pigment in the IHC slides, but also considers morphologic factors such as lymphocyte conglomerates. Overall, end-to-end weakly supervised DL shows potential for improving patient stratification for cancer immunotherapy by analyzing PD-L1 IHC, holistically integrating morphology and PD-L1 staining intensity. SIGNIFICANCE: The weakly supervised DL model to predict PD-L1 status from raw IHC data, integrating tumor staining intensity and morphology, enables enhanced patient stratification in cancer immunotherapy compared with traditional pathologist assessment.

Early-Stage Breast Cancer Detection in Breast Milk.

Breast cancer occurring during pregnancy (PrBC) and postpartum (PPBC) is usually diagnosed at more advanced stages compared with other breast cancer, worsening its prognosis. PPBC is particularly aggressive, with increased metastatic risk and mortality. Thus, effective screening methods to detect early PrBC and PPBC are needed. We report for the first time that cell-free tumor DNA (ctDNA) is present in breast milk (BM) collected from patients with breast cancer. Analysis of ctDNA from BM detects tumor variants in 87% of the cases by droplet digital PCR, while variants remain undetected in 92% of matched plasma samples. Retrospective next-generation sequencing analysis in BM ctDNA recapitulates tumor variants, with an overall clinical sensitivity of 71.4% and specificity of 100%. In two cases, ctDNA was detectable in BM collected 18 and 6 months prior to standard diagnosis. Our results open up the potential use of BM as a new source for liquid biopsy for PPBC detection. SIGNIFICANCE: For the first time, we show that BM obtained from patients with breast cancer carries ctDNA, surpassing plasma-based liquid biopsy for detection and molecular profiling of early-stage breast cancer, even prior to diagnosis by image. See related commentary by Cunningham and Turner, p. 2125. This article is featured in Selected Articles from This Issue, p. 2109.

DPPA3-HIF1α axis controls colorectal cancer chemoresistance by imposing a slow cell-cycle phenotype.

Tumor relapse is linked to rapid chemoresistance and represents a bottleneck for cancer therapy success. Engagement of a reduced proliferation state is a non-mutational mechanism exploited by cancer cells to bypass therapy-induced cell death. Through combining functional pulse-chase experiments in engineered cells and transcriptomic analyses, we identify DPPA3 as a master regulator of slow-cycling and chemoresistant phenotype in colorectal cancer (CRC). We find a vicious DPPA3-HIF1α feedback loop that downregulates FOXM1 expression via DNA methylation, thereby delaying cell-cycle progression. Moreover, downregulation of HIF1α partially restores a chemosensitive proliferative phenotype in DPPA3-overexpressing cancer cells. In cohorts of CRC patient samples, DPPA3 overexpression acts as a predictive biomarker of chemotherapeutic resistance that subsequently requires reduction in its expression to allow metastatic outgrowth. Our work demonstrates that slow-cycling cancer cells exploit a DPPA3/HIF1α axis to support tumor persistence under therapeutic stress and provides insights on the molecular regulation of disease progression.

A pan-cancer clinical platform to predict immunotherapy outcomes and prioritize immuno-oncology combinations in early-phase trials.

BACKGROUND: Immunotherapy is effective, but current biomarkers for patient selection have proven modest sensitivity. Here, we developed VIGex, an optimized gene signature based on the expression level of 12 genes involved in immune response with RNA sequencing. METHODS: We implemented VIGex using the nCounter platform (Nanostring) on a large clinical cohort encompassing 909 tumor samples across 45 tumor types. VIGex was developed as a continuous variable, with cutoffs selected to detect three main categories (hot, intermediate-cold and cold) based on the different inflammatory status of the tumor microenvironment. FINDINGS: Hot tumors had the highest VIGex scores and exhibited an increased abundance of tumor-infiltrating lymphocytes as compared with the intermediate-cold and cold. VIGex scores varied depending on tumor origin and anatomic site of metastases, with liver metastases showing an immunosuppressive tumor microenvironment. The predictive power of VIGex-Hot was observed in a cohort of 98 refractory solid tumor from patients treated in early-phase immunotherapy trials and its clinical performance was confirmed through an extensive metanalysis across 13 clinically annotated gene expression datasets from 877 patients treated with immunotherapy agents. Last, we generated a pan-cancer biomarker platform that integrates VIGex categories with the expression levels of immunotherapy targets under development in early-phase clinical trials. CONCLUSIONS: Our results support the clinical utility of VIGex as a tool to aid clinicians for patient selection and personalized immunotherapy interventions. FUNDING: BBVA Foundation; 202-2021 Division of Medical Oncology and Hematology Fellowship award; Princess Margaret Cancer Center.

Expression of TILs and Patterns of Gene Expression from Paired Samples of Malignant Pleural Mesothelioma (MPM) Patients.

MPM is an aggressive disease with an immunosuppressive tumor microenvironment, and interest in exploring immunotherapy in this disease has been increasing. In the first line of treatment, the combination of nivolumab and ipilimumab demonstrated an improvement in survival over chemotherapy. The presence of TILs has been recognized as a marker of antitumor immune response to chemotherapy in solid tumors. The aim of our study is to identify the effect of treatment on immune cells and the immune gene profile in MPM. We investigated the changes in expression of TILs in 10 human MPM paired tumor tissues using immunohistochemistry and gene expression analysis from paired untreated and treated samples. In this small series, we demonstrated that during the evolution of disease without any treatment there was an increase in the inflammatory component in tumor samples. After systemic treatment there was a decrease in the number of TILs. We observed that after systemic treatment or disease progression immune gene signatures were suppressed. Our integrated analysis of paired samples with immune profile and genomic changes on MPM suggested that during the evolution of the disease the immune system tends to switch, turning off with treatment.

RAGE/SNAIL1 signaling drives epithelial-mesenchymal plasticity in metastatic triple-negative breast cancer.

Epithelial/Mesenchymal (E/M) plasticity plays a fundamental role both in embryogenesis and during tumorigenesis. The receptor for advanced glycation end products (RAGE) is a driver of cell plasticity in fibrotic diseases; however, its role and molecular mechanism in triple-negative breast cancer (TNBC) remains unclear. Here, we demonstrate that RAGE signaling maintains the mesenchymal phenotype of aggressive TNBC cells by enforcing the expression of SNAIL1. Besides, we uncover a crosstalk mechanism between the TGF-ß and RAGE pathways that is required for the acquisition of mesenchymal traits in TNBC cells. Consistently, RAGE inhibition elicits epithelial features that block migration and invasion capacities. Next, since RAGE is a sensor of the tumor microenvironment, we modeled acute acidosis in TNBC cells and showed it promotes enhanced production of RAGE ligands and the activation of RAGE-dependent invasive properties. Furthermore, acute acidosis increases SNAIL1 levels and tumor cell invasion in a RAGE-dependent manner. Finally, we demonstrate that in vivo inhibition of RAGE reduces metastasis incidence and expands survival, consistent with molecular effects that support the relevance of RAGE signaling in E/M plasticity. These results uncover new molecular insights on the regulation of E/M phenotypes in cancer metastasis and provide rationale for pharmacological intervention of this signaling axis.

Impact of the COVID-19 pandemic in the early-onset colorectal cancer.

The COVID19 pandemic has affected the spectrum of cancer care worldwide. Early onset colorectal cancer (EOCRC) is defined as diagnosis below the age of 50. Patients with EOCRC faced multiple challenges during the COVID19 pandemic and in some institutions it jeopardized cancer diagnosis and care delivery. Our study aims to identify the clinicopathological features and outcomes of patients with EOCRC in our Centre during the first wave of the pandemic in comparison with the same period in 2019 and 2021. Patients with EOCRC visited for the first time at Vall d'Hebron University Hospital in Spain from the 1st March to 31st August of 2019, 2020 and 2021 were included in the analysis. 177 patients with EOCRC were visited for the first time between 2019 and 2021, of which 90 patients met the inclusion criteria (2019: 30 patients, 2020: 29 patients, 2021: 31 patients). Neither differences in frequency nor in stage at diagnosis or at first visit during the given periods were observed. Of note, indication of systemic therapy in the adjuvant or metastatic setting was not altered. Days to treatment initiation and enrollment in clinical trials in this subpopulation was not affected due to the COVID-19 outbreak.

Impact of Anti-HER2 Therapy Alone and With Weekly Paclitaxel on the Ovarian Reserve of Young Women With HER2-Positive Breast Cancer.

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<.001). At baseline, median AMH levels were 1.29 ng/mL (IQR, 0.56-2.62 ng/mL). At week 2, a small but significant reduction in AMH levels was observed (median, 1.10 ng/mL; IQR, 0.45-2.09 ng/mL; P<.001). At surgery, a larger significant decline in AMH levels was observed (median, 0.01 ng/mL; IQR, 0.01-0.03 ng/mL; P<.001). Although the type of anti-HER2 treatment (trastuzumab and/or lapatinib) did not seem to impact the results, age and pretreatment ovarian reserve had a major influence on treatment-induced gonadotoxicity risk. CONCLUSIONS: This NeoALTTO biomarker analysis showed that anti-HER2 therapies alone had limited gonadotoxicity but that the addition of weekly paclitaxel resulted in marked AMH decline with possible negative implications for subsequent ovarian function and fertility.

Ten-year survival of neoadjuvant dual HER2 blockade in patients with HER2-positive breast cancer.

BACKGROUND: Dual anti-HER2-targeted therapy in breast cancer (BC) significantly increased the rate of pathological complete response (pCR) compared to single blockade when added to chemotherapy. However, limited data exist on the long-term impact on survival of the additional increase in pCR. METHODS: Neoadjuvant lapatinib and/or trastuzumab treatment optimisation (NCT00553358) is an international, randomised, open-label, phase III study investigating the addition of lapatinib to chemotherapy plus trastuzumab in HER2-positive early BC. Ten-year event-free survival (EFS), overall survival (OS) and safety were assessed on intention-to-treat population. The association between pCR and EFS or OS was investigated in landmark population. RESULTS: A total of 455 patients were randomised to receive lapatinib (154), trastuzumab (149) or the combination (152). Ten-year EFS estimates were 63% (95% confidence interval [CI], 54%-71%) in the lapatinib group, 64% (95% CI, 55%-72%) in the trastuzumab group and 67% (95% CI, 58%-74%) in the combination group. Ten-year OS rates were 76% (95% CI, 67%-83%), 75% (95% CI, 66%-82%) and 80% (95% CI, 73%-86%) in the lapatinib, trastuzumab and combination groups, respectively. Women who achieved a pCR had improved EFS (hazard ratio 0.48, 95% CI, 0.31-0.73) and OS (hazard ratio 0.37, 95% CI, 0.20-0.63) compared with those who did not. The numerical difference in survival according to pCR status was greater in women treated with the combination and those with hormone-receptor-negative tumours. There were no new or long-term safety concerns. CONCLUSIONS: Patients with HER2-positive BC showed a durable survival benefit of neoadjuvant anti-HER2, irrespective of treatment arm. Patients who achieve pCR have significantly better outcomes than patients without pCR.

Prognostic and Predictive Value of Immune-Related Gene Expression Signatures vs Tumor-Infiltrating Lymphocytes in Early-Stage ERBB2/HER2-Positive Breast Cancer: A Correlative Analysis of the CALGB 40601 and PAMELA Trials.

Importance: Both tumor-infiltrating lymphocytes (TILs) assessment and immune-related gene expression signatures by RNA profiling predict higher pathologic complete response (pCR) and improved event-free survival (EFS) in patients with early-stage ERBB2/HER2-positive breast cancer. However, whether these 2 measures of immune activation provide similar or additive prognostic value is not known. Objective: To examine the prognostic ability of TILs and immune-related gene expression signatures, alone and in combination, to predict pCR and EFS in patients with early-stage ERBB2/HER2-positive breast cancer treated in 2 clinical trials. Design, Setting, and Participants: In this prognostic study, a correlative analysis was performed on the Cancer and Leukemia Group B (CALGB) 40601 trial and the PAMELA trial. In the CALGB 40601 trial, 305 patients were randomly assigned to weekly paclitaxel with trastuzumab, lapatinib, or both for 16 weeks. The primary end point was pCR, with a secondary end point of EFS. In the PAMELA trial, 151 patients received neoadjuvant treatment with trastuzumab and lapatinib for 18 weeks. The primary end point was the ability of the HER2-enriched subtype to predict pCR. The studies were conducted from October 2013 to November 2015 (PAMELA) and from December 2008 to February 2012 (CALGB 40601). Data analyses were performed from June 1, 2020, to January 1, 2022. Main Outcomes and Measures: Immune-related gene expression profiling by RNA sequencing and TILs were assessed on 230 CALGB 40601 trial pretreatment tumors and 138 PAMELA trial pretreatment tumors. The association of these biomarkers with pCR (CALGB 40601 and PAMELA) and EFS (CALGB 40601) was studied by logistic regression and Cox analyses. Results: The median age of the patients was 50 years (IQR, 42-50 years), and 305 (100%) were women. Of 202 immune signatures tested, 166 (82.2%) were significantly correlated with TILs. In both trials combined, TILs were significantly associated with pCR (odds ratio, 1.01; 95% CI, 1.01-1.02; P = .02). In addition to TILs, 36 immune signatures were significantly associated with higher pCR rates. Seven of these signatures outperformed TILs for predicting pCR, 6 of which were B-cell related. In a multivariable Cox model adjusted for clinicopathologic factors, including PAM50 intrinsic tumor subtype, the immunoglobulin G signature, but not TILs, was independently associated with EFS (immunoglobulin G signature-adjusted hazard ratio, 0.63; 95% CI, 0.42-0.93; P = .02; TIL-adjusted hazard ratio, 1.00; 95% CI, 0.98-1.02; P = .99). Conclusions and Relevance: Results of this study suggest that multiple B-cell-related signatures were more strongly associated with pCR and EFS than TILs, which largely represent T cells. When both TILs and gene expression are available, the prognostic value of immune-related signatures appears to be superior.

Human Metastatic Cholangiocarcinoma Patient-Derived Xenografts and Tumoroids for Preclinical Drug Evaluation.

PURPOSE: Cholangiocarcinoma (CCA) is usually diagnosed at advanced stages, with limited therapeutic options. Preclinical models focused on unresectable metastatic CCA are necessary to develop rational treatments. Pathogenic mutations in IDH1/2, ARID1A/B, BAP1, and BRCA1/2 have been identified in 30%-50% of patients with CCA. Several types of tumor cells harboring these mutations exhibit homologous recombination deficiency (HRD) phenotype with enhanced sensitivity to PARP inhibitors (PARPi). However, PARPi treatment has not yet been tested for effectiveness in patient-derived models of advanced CCA. EXPERIMENTAL DESIGN: We have established a collection of patient-derived xenografts from patients with unresectable metastatic CCA (CCA_PDX). The CCA_PDXs were characterized at both histopathologic and genomic levels. We optimized a protocol to generate CCA tumoroids from CCA_PDXs. We tested the effects of PARPis in both CCA tumoroids and CCA_PDXs. Finally, we used the RAD51 assay to evaluate the HRD status of CCA tissues. RESULTS: This collection of CCA_PDXs recapitulates the histopathologic and molecular features of their original tumors. PARPi treatments inhibited the growth of CCA tumoroids and CCA_PDXs with pathogenic mutations of BRCA2, but not those with mutations of IDH1, ARID1A, or BAP1. In line with these findings, only CCA_PDX and CCA patient biopsy samples with mutations of BRCA2 showed RAD51 scores compatible with HRD. CONCLUSIONS: Our results suggest that patients with advanced CCA with pathogenic mutations of BRCA2, but not those with mutations of IDH1, ARID1A, or BAP1, are likely to benefit from PARPi therapy. This collection of CCA_PDXs provides new opportunities for evaluating drug response and prioritizing clinical trials.

pTINCR microprotein promotes epithelial differentiation and suppresses tumor growth through CDC42 SUMOylation and activation.

The human transcriptome contains thousands of small open reading frames (sORFs) that encode microproteins whose functions remain largely unexplored. Here, we show that TINCR lncRNA encodes pTINCR, an evolutionary conserved ubiquitin-like protein (UBL) expressed in many epithelia and upregulated upon differentiation and under cellular stress. By gain- and loss-of-function studies, we demonstrate that pTINCR is a key inducer of epithelial differentiation in vitro and in vivo. Interestingly, low expression of TINCR associates with worse prognosis in several epithelial cancers, and pTINCR overexpression reduces malignancy in patient-derived xenografts. At the molecular level, pTINCR binds to SUMO through its SUMO interacting motif (SIM) and to CDC42, a Rho-GTPase critical for actin cytoskeleton remodeling and epithelial differentiation. Moreover, pTINCR increases CDC42 SUMOylation and promotes its activation, triggering a pro-differentiation cascade. Our findings suggest that the microproteome is a source of new regulators of cell identity relevant for cancer.

The conundrum of breast cancer and microbiome - A comprehensive review of the current evidence.

Disturbance of the microbial balance of a habitat can have detrimental effects on the health of the individual and, in addition, polymorphic microbiomes were recently suggested as emerging cancer hallmarks. Modern sequencing and metagenomics techniques have allowed characterization of intratumoral microbiome composition even in tissues such as the breast. We conducted a comprehensive literature review on different aspects related to the microbial landscape of the breast tissue and breast tumors, as well as its relation to systemic therapy. Emerging data suggest varying microbiome composition intratumorally compared to the normal breast tissue and other tumor types. Differences in the microbes present in normal breast and cancerous lesions of the breast have also been described, as well as potential correlation between microbiome composition and breast cancer subtype and stage. The interplay between gut and breast microbiome is not well understood although bacterial allocation through mesenteric lymph nodes has been suggested as a possible pathway. Moreover, gut bacteria with estrogen metabolizing properties are of special interest in the context of breast cancer and available knowledge and reported studies are hereby described. The relationship of gut microbiome and cancer therapy is another aspect of interest and available data are presented. Notwithstanding, the field of microbiome in the context of breast cancer is starting to evolve and a number of questions arise, with the gut-breast-cancer therapy axis in the center.

High p16 expression and heterozygous RB1 loss are biomarkers for CDK4/6 inhibitor resistance in ER+ breast cancer.

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.

RNF43 mutations predict response to anti-BRAF/EGFR combinatory therapies in BRAFV600E metastatic colorectal cancer.

Anti-BRAF/EGFR therapy was recently approved for the treatment of metastatic BRAFV600E colorectal cancer (mCRCBRAF-V600E). However, a large fraction of patients do not respond, underscoring the need to identify molecular determinants of treatment response. Using whole-exome sequencing in a discovery cohort of patients with mCRCBRAF-V600E treated with anti-BRAF/EGFR therapy, we found that inactivating mutations in RNF43, a negative regulator of WNT, predict improved response rates and survival outcomes in patients with microsatellite-stable (MSS) tumors. Analysis of an independent validation cohort confirmed the relevance of RNF43 mutations to predicting clinical benefit (72.7% versus 30.8%; P = 0.03), as well as longer progression-free survival (hazard ratio (HR), 0.30; 95% confidence interval (CI), 0.12-0.75; P = 0.01) and overall survival (HR, 0.26; 95% CI, 0.10-0.71; P = 0.008), in patients with MSS-RNF43mutated versus MSS-RNF43wild-type tumors. Microsatellite-instable tumors invariably carried a wild-type-like RNF43 genotype encoding p.G659fs and presented an intermediate response profile. We found no association of RNF43 mutations with patient outcomes in a control cohort of patients with MSS-mCRCBRAF-V600E tumors not exposed to anti-BRAF targeted therapies. Overall, our findings suggest a cross-talk between the MAPK and WNT pathways that may modulate the antitumor activity of anti-BRAF/EGFR therapy and uncover predictive biomarkers to optimize the clinical management of these patients.