Genetic Heterogeneity in Therapy-Naïve Synchronous Primary Breast Cancers and Their Metastases

Genetic Intratumor Heterogeneity Remodels the Immune Microenvironment and Induces Immune Evasion in Brain Metastasis of Lung Cancer

INTRODUCTION

Brain metastasis, with the highest incidence in patients with lung cancer, significantly worsens prognosis and poses challenges to clinical management. To date, how brain metastasis evades immune elimination remains unknown.

METHODS

Whole-exome sequencing and RNA sequencing were performed on 30 matched brain metastasis, primary lung adenocarcinoma, and normal tissues. Data from The Cancer Genome Atlas primary lung adenocarcinoma cohort, including multiplex immunofluorescence, were used to support the findings of bioinformatics analysis.

RESULTS

Our study highlights the key role of intratumor heterogeneity of genomic alterations in the metastasis process, mainly caused by homologous recombination deficiency or other somatic copy number alteration-associated mutation mechanisms, leading to increased genomic instability and genomic complexity. We further proposed a selection model of brain metastatic evolution in which intratumor heterogeneity drives immune remodeling, leading to immune escape through different mechanisms under local immune pressure.

CONCLUSIONS

Our findings provide novel insights into the metastatic process and immune escape mechanisms of brain metastasis and pave the way for precise immunotherapeutic strategies for patients with lung cancer with brain metastasis.

The enrichment of Fanconi anemia/homologous recombination pathway aberrations in ATM/ATR-mutated NSCLC was accompanied by unique molecular features and poor prognosis

BACKGROUND

ATM and ATR are two critical factors to regulate DNA damage response (DDR), and their mutations were frequently observed in different types of cancer, including non-small cell lung cancer (NSCLC). Given that the majority of identified ATM/ATR mutations were variants of uncertain significance, the clinical/molecular features of pathogenic ATM/ATR aberrations have not been comprehensively investigated in NSCLC.

METHODS

Next-generation sequencing (NGS) analyses were conducted to investigate the molecular features in 191 NSCLC patients who harbored pathogenic/likely pathogenic ATM/ATR mutations and 308 NSCLC patients who did not have any types of ATM/ATR variants. The results were validated using an external cohort of 2727 NSCLC patients (including 48 with ATM/ATR pathogenic mutations).

RESULTS

Most pathogenic ATM/ATR genetic alterations were frameshift and nonsense mutations that disrupt critical domains of the two proteins. ATM/ATR-mutated patients had significantly higher tumor mutational burdens (TMB; P < 0.001) and microsatellite instabilities (MSI; P = 0.023), but not chromosomal instabilities, than those without any ATM/ATR variations. In particular, KRAS mutations were significantly enriched in ATM-mutated patients (P = 0.014), whereas BRCA2 mutations (P = 0.014), TP53 mutations (P = 0.014), and ZNF703 amplification (P = 0.008) were enriched in ATR-mutated patients. Notably, patients with ATM/ATR pathogenic genetic alterations were likely to be accompanied by mutations in Fanconi anemia (FA) and homologous recombination (HR) pathways, which were confirmed using both the study (P < 0.001) and validation (P < 0.001) cohorts. Furthermore, the co-occurrence of FA/HR aberrations could contribute to increased TMB and MSI, and patients with both ATM/ATR and FA/HR mutations tended to have worse overall survival.

CONCLUSIONS

Our results demonstrated the unique clinical and molecular features of pathogenic ATM/ATR mutations in NSCLC, which helps better understand the cancerous involvement of these DDR regulators, as well as directing targeted therapies and/or immunotherapies to treat ATM/ATR-mutated NSCLC, especially those with co-existing FA/HR aberrations.

Predicting diagnosis and survival of bone metastasis in breast cancer using machine learning

This study aimed at establishing more accurate predictive models based on novel machine learning algorithms, with the overarching goal of providing clinicians with effective decision-making assistance. We retrospectively analyzed the breast cancer patients recorded in the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2016. Multivariable logistic regression analyses were used to identify risk factors for bone metastases in breast cancer, whereas Cox proportional hazards regression analyses were used to identify prognostic factors for breast cancer with bone metastasis (BCBM). Based on the identified risk and prognostic factors, we developed diagnostic and prognostic models that incorporate six machine learning classifiers. We then used the area under the receiver operating characteristic (ROC) curve (AUC), learning curve, precision curve, calibration plot, and decision curve analysis to evaluate performance of the machine learning models. Univariable and multivariable logistic regression analyses showed that bone metastases were significantly associated with age, race, sex, grade, T stage, N stage, surgery, radiotherapy, chemotherapy, tumor size, brain metastasis, liver metastasis, lung metastasis, breast subtype, and PR. Univariate and multivariate Cox regression analyses revealed that age, race, marital status, grade, surgery, radiotherapy, chemotherapy, brain metastasis, liver metastasis, lung metastasis, breast subtype, ER, and PR were closely associated with the prognosis of BCBM. Among the six machine learning models, the XGBoost algorithm predicted the most accurate results (Diagnostic model AUC = 0.98; Prognostic model AUC = 0.88). According to the Shapley additive explanations (SHAP), the most critical feature of the diagnostic model was surgery, followed by N stage. Interestingly, surgery was also the most critical feature of prognostic model, followed by liver metastasis. Based on the XGBoost algorithm, we could effectively predict the diagnosis and survival of bone metastasis in breast cancer and provide targeted references for the treatment of BCBM patients.

Cancer metastasis: Molecular mechanisms and clinical perspectives

Metastatic progression combined with non-responsiveness towards systemic therapy often shapes the course of disease for cancer patients and commonly determines its lethal outcome. The complex molecular events that promote metastasis are a combination of both, the acquired pro-metastatic properties of cancer cells and a metastasis-permissive or -supportive tumor micro-environment (TME). Yet, dissemination is a challenging process for cancer cells that requires a series of events to enable cancer cell survival and growth. Metastatic cancer cells have to initially detach themselves from primary tumors, overcome the challenges of their intravasal journey and colonize distant sites that are suited for their metastases. The implicated obstacles including anoikis and immune surveillance, can be overcome by intricate intra- and extracellular signaling pathways, which we will summarize and discuss in this review. Further, emerging modulators of metastasis, like the immune-microenvironment, microbiome, sublethal cell death engagement, or the nervous system will be integrated into the existing working model of metastasis.

Associations amongst genes, molecules, cells, and organs in breast cancer metastasis

This paper is a cross fertilization of ideas about the importance of molecular aspects of breast cancer metastasis by basic scientists, a pathologist, and clinical oncologists at the Henry Ford Health symposium. We address four major topics: (i) the complex roles of lymphatic endothelial cells and the molecules that stimulate them to enhance lymph node and systemic metastasis and influence the anti-tumor immunity that might inhibit metastasis; (ii) the interaction of molecules and cells when breast cancer spreads to bone, and how bone metastases may themselves spread to internal viscera; (iii) how molecular expression and morphologic subtypes of breast cancer assist clinicians in determining which patients to treat with more or less aggressive therapies; (iv) how the outcomes of patients with oligometastases in breast cancer are different from those with multiple metastases and how that could justify the aggressive treatment of these patients with the hope of cure.

Breast cancers as ecosystems: a metabolic perspective

Breast cancer (BC) is the most frequently diagnosed cancer and one of the major causes of cancer death. Despite enormous progress in its management, both from the therapeutic and early diagnosis viewpoints, still around 700,000 patients succumb to the disease each year, worldwide. Late recurrency is the major problem in BC, with many patients developing distant metastases several years after the successful eradication of the primary tumor. This is linked to the phenomenon of metastatic dormancy, a still mysterious trait of the natural history of BC, and of several other types of cancer, by which metastatic cells remain dormant for long periods of time before becoming reactivated to initiate the clinical metastatic disease. In recent years, it has become clear that cancers are best understood if studied as ecosystems in which the impact of non-cancer-cell-autonomous events-dependent on complex interaction between the cancer and its environment, both local and systemic-plays a paramount role, probably as significant as the cell-autonomous alterations occurring in the cancer cell. In adopting this perspective, a metabolic vision of the cancer ecosystem is bound to improve our understanding of the natural history of cancer, across space and time. In BC, many metabolic pathways are coopted into the cancer ecosystem, to serve the anabolic and energy demands of the cancer. Their study is shedding new light on the most critical aspect of BC management, of metastatic dissemination, and that of the related phenomenon of dormancy and fostering the application of the knowledge to the development of metabolic therapies.

Imagine beyond: recent breakthroughs and next challenges in mammary gland biology and breast cancer research

On 8 December 2022 the organizing committee of the European Network for Breast Development and Cancer labs (ENBDC) held its fifth annual Think Tank meeting in Amsterdam, the Netherlands. Here, we embraced the opportunity to look back to identify the most prominent breakthroughs of the past ten years and to reflect on the main challenges that lie ahead for our field in the years to come. The outcomes of these discussions are presented in this position paper, in the hope that it will serve as a summary of the current state of affairs in mammary gland biology and breast cancer research for early career researchers and other newcomers in the field, and as inspiration for scientists and clinicians to move the field forward.

Deciphering Common Traits of Breast and Ovarian Cancer Stem Cells and Possible Therapeutic Approaches

Breast cancer (BC) and ovarian cancer (OC) are among the most common and deadly cancers affecting women worldwide. Both are complex diseases with marked heterogeneity. Despite the induction of screening programs that increase the frequency of earlier diagnosis of BC, at a stage when the cancer is more likely to respond to therapy, which does not exist for OC, more than 50% of both cancers are diagnosed at an advanced stage. Initial therapy can put the cancer into remission. However, recurrences occur frequently in both BC and OC, which are highly cancer-subtype dependent. Therapy resistance is mainly attributed to a rare subpopulation of cells, named cancer stem cells (CSC) or tumor-initiating cells, as they are capable of self-renewal, tumor initiation, and regrowth of tumor bulk. In this review, we will discuss the distinctive markers and signaling pathways that characterize CSC, their interactions with the tumor microenvironment, and the strategies they employ to evade immune surveillance. Our focus will be on identifying the common features of breast cancer stem cells (BCSC) and ovarian cancer stem cells (OCSC) and suggesting potential therapeutic approaches.

Deep learning model accurately classifies metastatic tumors from primary tumors based on mutational signatures

Metastatic propagation is the leading cause of death for most cancers. Prediction and elucidation of metastatic process is crucial for the treatment of cancer. Even though somatic mutations have been linked to tumorigenesis and metastasis, it is less explored whether metastatic events can be identified through genomic mutational signatures, which are concise descriptions of the mutational processes. Here, we developed MetaWise, a Deep Neural Network (DNN) model, by applying mutational signatures as input features calculated from Whole-Exome Sequencing (WES) data of TCGA and other metastatic cohorts. This model can accurately classify metastatic tumors from primary tumors and outperform traditional machine learning (ML) models and a deep learning (DL) model, DiaDeL. Signatures of non-coding mutations also have a major impact on the model's performance. SHapley Additive exPlanations (SHAP) and Local Surrogate (LIME) analyses identify several mutational signatures which are directly correlated to metastatic spread in cancers, including APOBEC-mutagenesis, UV-induced signatures, and DNA damage response deficiency signatures.

Rare mutation-dominant compound EGFR-positive NSCLC is associated with enriched kinase domain-resided variants of uncertain significance and poor clinical outcomes

BACKGROUND

Compound epidermal growth factor receptor (EGFR) mutations are less responsive to tyrosine kinase inhibitors (TKIs) than single EGFR mutations in non-small cell lung cancer (NSCLC). However, the detailed clinical characteristics and prognosis of various compound EGFR mutations remain to be elucidated.

METHODS

We retrospectively studied the next-generation sequencing (NGS) data of treatment-naïve tumors from 1025 NSCLC patients with compound EGFR mutations, which were sub-categorized into different combinations of common mutations (19-Del and EGFR exon 21 p.L858R), rare mutations, and variants of uncertain significance (VUSs). Prognosis and drug resistance to first-line TKIs were analyzed in 174 and 95 patients, respectively.

RESULTS

Compound EGFR mutations were enriched with EGFR exon 21 p.L858R and rare mutations, but not 19-Del (P < 0.001). The common + rare and rare + rare subtypes had fewer concurrent mutations in the PI3K pathway (P = 0.032), while the rare + rare and common + VUSs subtypes showed increased association with smoking- and temozolomide-related mutational signatures, respectively (P < 0.001). The rare mutation-dominant subtypes (rare + VUSs and rare + rare) had the worst clinical outcomes to first-line TKIs (P < 0.001), which was further confirmed using an external cohort (P = 0.0066). VUSs in the rare + VUSs subtype selectively reside in the EGFR kinase domain (P < 0.001), implying these tumors might select additional mutations to disrupt the regulation/function of the kinase domain.

CONCLUSIONS

Different subtypes of compound EGFR mutations displayed distinct clinical features and genetic architectures, and rare mutation-dominant compound EGFR mutations were associated with enriched kinase domain-resided VUSs and poor clinical outcomes. Our findings help better understand the oncogenesis of compound EGFR mutations and forecast prognostic outcomes of personalized treatments.

Stem Cell Theory of Cancer: Origin of Metastasis and Sub-clonality

Metastasis may be the secret weapon cancer uses to dominate and subjugate, to persist and prevail. However, it is no longer a secret when we realize that a stem cell has the same ways and means to fulfill its own omnipotence and accomplish its own omnipresence… and when we realize that a cancer cell has its own version of stem-ness origin and stem-like nature. In this perspective, we discuss whether stem-ness enables metastasis or mutations drive metastasis. We ponder about low-grade versus high-grade tumors and about primary versus metastatic tumors. We wonder about stochasticity and hierarchy in the genesis and evolution of cancer and of metastasis. We postulate that metastasis may hold the elusive code that makes or breaks a stem-cell versus a genetic theory of cancer. We speculate that the vaunted model of multistep carcinogenesis may be in error and needs some belated remodeling and a major overhaul. We propose that subsequent malignant neoplasms from germ cell tumors and donor-derived malignancies in organ transplants are quintessential experiments of nature and by man that may eventually empower us to elucidate a stem-cell origin of cancer and metastasis. Unfortunately, even the best experiments of cancer and of metastasis will be left unfinished, overlooked, or forgotten, when we do not formulate a proper cancer theory derived from pertinent and illuminating clinical observations. Ultimately, there should be no consternations when we realize that metastasis has a stem-cell rather than a genetic origin, and no reservations when we recognize that metastasis has been providing us some of the most enduring tests and endearing proofs to demonstrate that cancer is indeed a stem-cell rather than a genetic disease after all.

Construction of a fatty acid metabolism-related gene signature for predicting prognosis and immune response in breast cancer

Background: Breast cancer has the highest incidence among malignant tumors in women, and its prevalence ranks first in global cancer morbidity. Aim: This study aimed to explore the feasibility of a prognostic model for patients with breast cancer based on the differential expression of genes related to fatty acid metabolism. Methods: The mRNA expression matrix of breast cancer and paracancer tissues was downloaded from The Cancer Genome Atlas database. The differentially expressed genes related to fatty acid metabolism were screened in R language. The TRRUST database was used to predict transcriptional regulators related to hub genes and construct an mRNA-transcription factor interaction network. A consensus clustering approach was used to identify different fatty acid regulatory patterns. In combination with patient survival data, Lasso and multivariate Cox proportional risk regression models were used to establish polygenic prognostic models based on fatty acid metabolism. The median risk score was used to categorize patients into high- and low-risk groups. Kaplan-Meier survival curves were used to analyze the survival differences between both groups. The Cox regression analysis included risk score and clinicopathological factors to determine whether risk score was an independent risk factor. Models based on genes associated with fatty acid metabolism were evaluated using receiver operating characteristic curves. A comparison was made between risk score levels and the fatty acid metabolism-associated genes in different subtypes of breast cancer. The differential gene sets of the Kyoto Encyclopedia of Genes and Genomes for screening high- and low-risk populations were compared using a gene set enrichment analysis. Furthermore, we utilized CIBERSORT to examine the abundance of immune cells in breast cancer in different clustering models. Results: High expression levels of ALDH1A1 and UBE2L6 prevented breast cancer, whereas high RDH16 expression levels increased its risk. Our comprehensive assessment of the association between prognostic risk scoring models and tumor microenvironment characteristics showed significant differences in the abundance of various immune cells between high- and low-risk breast cancer patients. Conclusions: By assessing fatty acid metabolism patterns, we gained a better understanding of the infiltration characteristics of the tumor microenvironment. Our findings are valuable for prognosis prediction and treatment of patients with breast cancer based on their clinicopathological characteristics.

A radiomic model to classify response to neoadjuvant chemotherapy in breast cancer

BACKGROUND

Medical image analysis has evolved to facilitate the development of methods for high-throughput extraction of quantitative features that can potentially contribute to the diagnostic and treatment paradigm of cancer. There is a need for further improvement in the accuracy of predictive markers of response to neo-adjuvant chemotherapy (NAC). The aim of this study was to develop a radiomic classifier to enhance current approaches to predicting the response to NAC breast cancer.

METHODS

Data on patients treated for breast cancer with NAC prior to surgery who had a pre-NAC dynamic contrast enhanced breast MRI were included. Response to NAC was assessed using the Miller-Payne system on the excised tumor. Tumor segmentation was carried out manually under the supervision of a consultant breast radiologist. Features were selected using least absolute shrinkage selection operator regression. A support vector machine learning model was used to classify response to NAC.

RESULTS

74 patients were included. Patients were classified as having a poor response to NAC (reduction in cellularity < 90%, n = 44) and an excellent response (> 90% reduction in cellularity, n = 30). 4 radiomics features (discretized kurtosis, NGDLM contrast, GLZLM_SZE and GLZLM_ZP) were identified as pertinent predictors of response to NAC. A SVM model using these features stratified patients into poor and excellent response groups producing an AUC of 0.75. Addition of estrogen receptor status improved the accuracy of the model with an AUC of 0.811.

CONCLUSION

This study identified a radiomic classifier incorporating 4 radiomics features to augment subtype based classification of response to NAC in breast cancer.

Discordance in receptor status between primary and metastatic breast cancer and overall survival: A single-center analysis

BACKGROUND

The tumor phenotype may change between primary and metastatic breast cancer. We compared the expression of estrogen receptor (ER), progesterone receptor (PR), and HER2 in a series of primary breast carcinomas (PBC) with their metastatic relapses and analyzed the impact of any changes on survival.

MATERIALS AND METHODS

It was a single-center retrospective study, collecting consecutive cases of metastatic breast carcinoma diagnosed in the pathology and medical oncology departments at Habib Bourguiba University Hospital in Sfax, Tunisia. An immunohistochemical study was used to assess ER, PR, and HER2 expression. Overall survival (OS) and post-metastasis survival (PMS) were evaluated using multivariable Cox regression analysis.

RESULTS

Our study included 68 patients. ER and PR status changed in 29.4 % and 39.7 % of cases, respectively. Conversions were mainly from positive to negative status (22 % and 23.5 % for ER and PR, respectively). Differences in HER2 status were observed in 19.6 % of cases, with loss of overexpression in 6 patients (10.7 %). Adjuvant trastuzumab therapy and PBC molecular subtype (HR-, HER2+) were associated with HER2 status discordance (p = 0.02 and 0.03, respectively). On multivariable analysis, HR-negative conversion tumors were significantly associated with a worse OS (p = 0.042) and PMS (p < 0.001), compared to HR-concordant positive tumors.

CONCLUSION

This study establishes that HR and HER2 status discordance between primary and metastatic breast carcinoma has a prognostic impact on patient outcome. Analyzing these receptors' status in all newly diagnosed cases of metastatic breast carcinoma is strongly recommended and would provide information for changing treatment strategies.

The Multi-Omic Landscape of Primary Breast Tumors and Their Metastases: Expanding the Efficacy of Actionable Therapeutic Targets

Breast cancer (BC) mortality is almost exclusively due to metastasis, which is the least understood aspect of cancer biology and represents a significant clinical challenge. Although we have witnessed tremendous advancements in the treatment for metastatic breast cancer (mBC), treatment resistance inevitably occurs in most patients. Recently, efforts in characterizing mBC revealed distinctive genomic, epigenomic and transcriptomic (multi-omic) landscapes to that of the primary tumor. Understanding of the molecular underpinnings of mBC is key to understanding resistance to therapy and the development of novel treatment options. This review summarizes the differential molecular landscapes of BC and mBC, provides insights into the genomic heterogeneity of mBC and highlights the therapeutically relevant, multi-omic features that may serve as novel therapeutic targets for mBC patients.

Targeted amplicon sequencing for primary tumors and matched lymph node metastases in patients with extrahepatic cholangiocarcinoma

BACKGROUND

Lymph node metastasis (LNM) is one of the most adverse prognostic factors in extrahepatic cholangiocarcinoma (EHCC) cases. As next-generation sequencing technology has become more widely available, the genomic profile of biliary tract carcinoma has been clarified. However, whether LNMs have additional genomic alterations in patients with EHCC has not been investigated. Here, we aimed to compare the genomic alterations between primary tumors and matched LNMs in patients with EHCC.

METHODS

Sixteen patients with node-positive EHCCs were included. Genomic DNA was extracted from tissue samples of primary tumors and matched LNMs. Targeted amplicon sequencing of 160 cancer-related genes was performed.

RESULTS

Among the 32 tumor samples from 16 patients, 91 genomic mutations were identified. Genomic mutations were noted in 31 genes, including TP53, MAP3K1, SMAD4, APC, and ARID1A. TP53 mutations were most frequently observed (12/32; 37.5%). Genomic mutation profiles were highly concordant between primary tumors and matched LNMs (13/16; 81.3%), and an additional genomic mutation of CDK12 was observed in only one patient.

CONCLUSION

Genomic mutations were highly concordant between primary tumors and matched LNMs, suggesting that genotyping of archived primary tumor samples may help predict genomic mutations of metastatic tumors in patients with EHCC.

Molecular Assessment of HER2 to Identify Signatures Associated with Therapy Response in HER2-Positive Breast Cancer

Simple Summary

The HER2 status of breast cancers is accurately determined by measuring HER2 protein overexpression and gene amplification. However, these clinical diagnostic tests cannot predict the response to therapy. Single molecule imaging approaches can quantify molecular features of HER2, such as receptor nano-organization, with exquisite spatial resolution and sensitivity. The aim of our study was to assess how the molecular features of HER2 varied with the therapy response. According to our results in cultured cell lines and six patient specimens, the therapy response was associated with high detected HER2 densities and clustering. This advanced imaging approach can thus provide key data to complement the current diagnostic standards.

Abstract

Trastuzumab, the prototype HER2-directed therapy, has markedly improved survival for women with HER2-positive breast cancers. However, only 40–60% of women with HER2-positive breast cancers achieve a complete pathological response to chemotherapy combined with HER2-directed therapy. The current diagnostic assays have poor positive-predictive accuracy in identifying therapy-responsive breast cancers. Here, we deployed quantitative single molecule localization microscopy to assess the molecular features of HER2 in a therapy-responsive setting. Using fluorescently labeled trastuzumab as a probe, we first compared the molecular features of HER2 in trastuzumab-sensitive (BT-474 and SK-BR-3) and trastuzumab-resistant (BT-474^R and JIMT-1) cultured cell lines. Trastuzumab-sensitive cells had significantly higher detected HER2 densities and clustering. We then evaluated HER2 in pre-treatment core biopsies from women with breast cancer undergoing neoadjuvant therapy. A complete pathological response was associated with a high detected HER2 density and significant HER2 clustering. These results established the nano-organization of HER2 as a potential signature of therapy-responsive disease.

Beyond Genetics: Metastasis as an Adaptive Response in Breast Cancer

Metastatic disease represents the primary cause of breast cancer (BC) mortality, yet it is still one of the most enigmatic processes in the biology of this tumor. Metastatic progression includes distinct phases: invasion, intravasation, hematogenous dissemination, extravasation and seeding at distant sites, micro-metastasis formation and metastatic outgrowth. Whole-genome sequencing analyses of primary BC and metastases revealed that BC metastatization is a non-genetically selected trait, rather the result of transcriptional and metabolic adaptation to the unfavorable microenvironmental conditions which cancer cells are exposed to (e.g., hypoxia, low nutrients, endoplasmic reticulum stress and chemotherapy administration). In this regard, the latest multi-omics analyses unveiled intra-tumor phenotypic heterogeneity, which determines the polyclonal nature of breast tumors and constitutes a challenge for clinicians, correlating with patient poor prognosis. The present work reviews BC classification and epidemiology, focusing on the impact of metastatic disease on patient prognosis and survival, while describing general principles and current in vitro/in vivo models of the BC metastatic cascade. The authors address here both genetic and phenotypic intrinsic heterogeneity of breast tumors, reporting the latest studies that support the role of the latter in metastatic spreading. Finally, the review illustrates the mechanisms underlying adaptive stress responses during BC metastatic progression.

Altered Signaling Pathways Revealed by Comprehensive Genomic Profiling in Patients With Unknown Primary Tumors

Purpose

Carcinoma of unknown primary (CUP) is a clinically aggressive disorder with early tumor dissemination. Identifying molecular traits of CUP can be not only beneficial for a better therapeutic approach but also potentially valuable for patients with general metastatic dissemination.

Patients and Methods

We retrospectively investigated a total of 35 unique CUP cases. Tumor tissue samples were available in 26 patients, and plasma samples were available in 22 patients. Targeted sequencing was performed with a panel of 416 pan cancer-related genes.

Results

A genomic landscape of the CUP cohort showed that TP53 mutation was the most frequently observed mutation while MYC amplification was the most common CNV. Aberrant TP53, RTK-RAS, and PI3K signaling pathways were also prevalent, identified in more than half of the cases with tumor tissue. Around 58% of the CUP cases harbored homologous recombinant repair (HRR) pathway gene alterations. The tumor mutational load of CUP patients with altered HRR pathway displayed a significant increase than that of patients with intact HRR. Clinically actionable mutations were identified in eight patients, which may benefit from targeted therapies. Eight patients were treated with platinum-based chemotherapy, showing different responses, HRR, and LOH status.

Conclusion

Collectively, our data have provided much-need insights into the treatment options for patients diagnosed with CUP in the era of precision medicine.

Heterogeneity and tumor evolution reflected in liquid biopsy in metastatic breast cancer patients: a review

Breast cancer is a spatially and temporally dynamic disease in which differently evolving genetic clones are responsible for progression and clinical outcome. We review tumor heterogeneity and clonal evolution from studies comparing primary tumors and metastasis and discuss plasma circulating tumor DNA as a powerful real-time approach for monitoring the clonal landscape of breast cancer during treatment and recurrence. We found only a few early studies exploring clonal evolution and heterogeneity through analysis of multiregional tissue biopsies of different progression steps in comparison with circulating tumor DNA (ctDNA) from blood plasma. The model of linear progression seemed to be more often reported than the model of parallel progression. The results show complex routes to metastasis, however, and plasma most often reflected metastasis more than primary tumor. The described patterns of evolution and the polyclonal nature of breast cancer have clinical consequences and should be considered during patient diagnosis and treatment selection. Current studies focusing on the relevance of clonal evolution in the clinical setting illustrate the role of liquid biopsy as a noninvasive biomarker for monitoring clonal progression and response to treatment. In the clinical setting, circulating tumor DNA may be an ideal support for tumor biopsies to characterize the genetic landscape of the metastatic disease and to improve longitudinal monitoring of disease dynamics and treatment effectiveness through detection of residual tumor after resection, relapse, or metastasis within a particular patient.

ELP6 and PLIN5 Mutations Were Probably Prognostic Biomarkers for Patients With Gastric Cancer

Purpose

Gastric cancer (GC) is the fifth leading cancer around world. And prognosis of patients with GC is still undesirable. Our study aimed to explore potential prognostic biomarkers for patients with GC.

Methods

The clinical samples were collected from the Qinghai University Affiliated Hospital, which were subjected to the whole exome sequencing (WES). The other GC-related data were obtained from The Cancer Genome Atlas (TCGA) database. Cross analyses were done to determine the candidate genes. And the final mutated genes were determined by survival analyses, univariate and multivariate Cox regression analyses. CIBERSORT and GSEA were used for immune cell infiltration analysis and functional enrichment, respectively.

Results

After cross analyses, 160 candidate-mutated genes were identified. And mutated ELP6 and PLIN5 were significantly independently correlated with the overall survival (OS) of patients with GC. Patients with GC with ELP6 and PLIN5 mutations had worse and better prognosis, respectively. Totally 5 types of immune cells were significantly differentially infiltrated in wild-type and mutated ELP6 and PLIN5 GC samples. In mutated ELP6 and PLIN5 GC samples, totally 7 and 11 pathways were significantly enriched, respectively.

Conclusions

The ELP6 and PLIN5 mutations were probably prognostic biomarkers for patients with GC.

Pathogenesis of Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) encompasses a heterogeneous group of fundamentally different diseases with different histologic, genomic, and immunologic profiles, which are aggregated under this term because of their lack of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 expression. Massively parallel sequencing and other omics technologies have demonstrated the level of heterogeneity in TNBCs and shed light into the pathogenesis of this therapeutically challenging entity in breast cancer. In this review, we discuss the histologic and molecular classifications of TNBC, the genomic alterations these different tumor types harbor, and the potential impact of these alterations on the pathogenesis of these tumors. We also explore the role of the tumor microenvironment in the biology of TNBCs and its potential impact on therapeutic response. Dissecting the biology and understanding the therapeutic dependencies of each TNBC subtype will be essential to delivering on the promise of precision medicine for patients with triple-negative disease.

Mutational landscape of paired primary and synchronous metastatic lymph node in chemotherapy naive gallbladder cancer

BACKGROUND

Comprehensive genomic analysis of paired primary tumors and their metastatic lesions may provide new insights into the biology of metastatic processes and therefore guide the development of novel strategies for intervention. To date, our knowledge of the genetic divergence and phylogenetic relationships in gallbladder cancer (GBC) is limited.

METHODS

We performed whole exome sequencing for 5 patients with primary tumor, metastatic lymph node (LNM) and corresponding normal tissue. Mutations, mutation signatures and copy number variations were analyzed with state-of-art bioinformatics methods. Phylogenetic tree was also generated to infer metastatic pattern.

RESULTS

Five driver mutations were detected in these patients. Among which, TP53 was the only shared mutation between primary tumor and LNM. Although tumor mutational burden was comparable between primary tumor and LNM, higher mutation burden was observed in LNM of one patient. Copy number variations (CNVs) burden was higher in LNM than their primary tumor. Phylogenetic analysis indicated both linear and parallel progression of metastasis exist in these patients. TP53 mutation and CNVs were homogenously between primary tumor and LNM.

CONCLUSIONS

High consistence of genetic landscape were shown between primary tumor and LNM in GBC. However, heterogenicity still exist between primary tumor and LNM in particular patients in term of driver mutation, TMB and CNV burden. Phylogenetic analysis indicated both Linear and parallel progression of metastasis were exist among these patients.

Research advances and new challenges in overcoming triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a pathological term used to identify invasive breast cancers that lack expression of estrogen and progesterone receptors and do not have pathologic overexpression of the HER2 receptor or harbor ERBB2 gene amplification. TNBC includes a collection of multiple distinct disease entities based upon genomic, transcriptomic and phenotypic characterization. Despite improved clinical outcomes with the development of novel therapeutics, TNBC still yields the worst prognosis among all clinical subtypes of breast cancer. We will systematically review evidence of the genomic evolution of TNBC, as well as potential mechanisms of disease progression and treatment resistance, defined in part by advances in next-generation DNA sequencing technology (including single cell sequencing), providing a new perspective on treatment strategies, and promise to reveal new potential therapeutic targets. Moreover, we review novel therapies aimed at homologous recombination deficiency, PI3 kinase/AKT/PTEN pathway activation, androgen receptor blockade, immune checkpoint inhibition, as well as antibody-drug conjugates engaging novel cell surface targets, including recent progress in pre-clinical and clinical studies which further validate the role of targeted therapies in TNBC. Despite major advances in treatment for TNBC, including FDA approval of 2 PARP inhibitors for metastatic TNBC, the crossing of the superiority boundary in a phase 3, placebo-controlled study of adjuvant olaparib in early-stage patients with germline BRCA-mutated high-risk HER2-negative early breast cancer, the FDA approval of 2 PD-(L)1 checkpoint antibodies for metastatic TNBC, and the FDA approval of the first antibody drug conjugate for TNBC, significant challenges remain. For example, despite the dawn of immunotherapy in metastatic TNBC, durable responses are limited to a small subset of patients, definitive biomarkers for patient selection are lacking, and the Oncology Drug Advisory Committee to the FDA has recently voted against approval of an anti-PD-1 checkpoint antibody high risk early-stage TNBC in the neoadjuvant setting. Also, despite early positive randomized phase 2 studies of AKT inhibition in metastatic TNBC, a recent phase 3 registration trial failed to validate earlier phase 2 data. Finally, we note that level one evidence for clinical efficacy of androgen receptor blockade in TNBC is still lacking. To meet these and other challenges, we will catalogue the ongoing exponential increase in interest in basic, translational, and clinical research to develop new treatment paradigms for TNBC.

TP53 mutations are associated with primary endocrine resistance in luminal early breast cancer

Background

Whereas the genomic landscape of endocrine‐resistant breast cancer has been intensely characterized in previously treated cases with local or distant recurrence, comparably little is known about genomic alterations conveying primary non‐responsiveness to endocrine treatment in luminal early breast cancer.

Methods

In this study, 622 estrogen receptor‐expressing breast cancer cases treated with short‐term preoperative endocrine therapy (pET) from the WSG‐ADAPT trial (NCT01779206) were analyzed for genetic alterations associated with impaired endocrine proliferative response (EPR) to 3‐week pET with tamoxifen or aromatase inhibitors. EPR was categorized as optimal (post‐pET Ki67 <10%) versus slightly, moderately, and severely impaired (post‐pET Ki67 10%–19%, 20%–34%, and ≥35%, respectively). Recently described gene mutations frequently found in previously treated advanced breast cancer were analyzed (ARID1A, BRAF, ERBB2, ESR1, GATA3, HRAS, KRAS, NRAS, PIK3CA, and TP53) by next‐generation sequencing. Amplifications of CCND1, FGFR1, ERBB2, and PAK1 were determined by digital PCR or fluorescence in situ hybridization.

Results

ERBB2 amplification (p = 0.0015) and mutations of TP53 (p < 0.0001) were significantly associated with impaired EPR. Impaired EPR in TP53‐mutated breast cancer cases was independent from the Oncotype DX Recurrence Score group and was seen both with tamoxifen‐ and aromatase inhibitor‐based pET (p = 0.0005 each).

Conclusion

We conclude that impaired EPR to pET is suitable to identify cases with primary endocrine resistance in early luminal breast cancer and that TP53‐mutated luminal cancers might not be sufficiently treated by endocrine therapy alone.

Diagnosis, biology and epidemiology of oligometastatic breast cancer

Does oligometastatic breast cancer (OMBC) deserve a dedicated treatment? Although some authors recommend multidisciplinary management of OMBC with a curative intent, there is no evidence proving this strategy beneficial in the absence of a randomized trial. The existing literature sheds little light on OMBC. Incidence is unknown; data available are either obsolete or biased; there is no consensus on the definition of OMBC and metastatic sites, nor on necessary imaging techniques. However, certain proposals merit consideration. Knowledge of eventual specific OMBC biological characteristics is limited to circulating tumor cell (CTC) counts. Given the data available for other cancers, studies on microRNAs (miRNAs), circulating tumor DNA (ctDNA) and genomic alterations should be developed Finally, safe and effective therapies do exist, but results of randomized trials will not be available for many years. Prospective observational cohort studies need to be implemented.

Biomarkers of Targeted Therapy and Immuno-Oncology in Cancers Metastatic to the Breast

The breast is a rare site for metastases, and their molecular characteristics have not been studied yet. Intrinsic molecular genetics, cancer characteristics, and breast tissue immune responses in diverse metastases to the breast have not been previously studied. We identified 64 patients with cancers metastatic to the breast: 51 carcinomas and 13 melanomas. Programmed death ligand 1 (PD-L1), steroid receptors, and HER2/neu expressions were evaluated using immunohistochemistry. Gene sequencing, copy number alterations, microsatellite instability, and tumor mutational burden were performed using next-generation sequencing platforms. The 3 most common primary sites for metastatic carcinomas were lung (37%), ovary (29%), and fallopian tubes/peritoneum (14%). TP53 mutations were commonly (50%) observed among the carcinoma cases, while other mutations were characteristic for the primary cancers (VHL in renal, BRCA1 in the fallopian tube, and BRAF in melanomas). High tumor mutational burden was detected in 5/14 carcinomas and 3/7 melanomas. Tumor cell PD-L1 expression was detected in 6 carcinomas, but not in any of the melanomas, whereas immune cells' expression of PD-L1 was seen in 17 carcinomas and 6 melanomas. Estrogen receptor status was positive in 13/49 carcinomas including 12 adenocarcinomas originating from the ovary and fallopian tube or peritoneum and 1 duodenal neuroendocrine carcinoma. No carcinoma was HER2/neu positive. Intrinsic genetic characteristics of the metastases to the breast followed the pattern commonly seen in primary tumors. Biomarkers of potential benefit to immune checkpoint inhibition therapy were limited to PD-L1-positive non-small cell lung cancer. No common characteristics of the heterogeneous group of tumor metastases to this organ were identified.

Somatic Copy Number Alterations in Human Cancers: An Analysis of Publicly Available Data From The Cancer Genome Atlas

Somatic copy number alterations (SCNAs) are a pervasive trait of human cancers that contributes to tumorigenesis by affecting the dosage of multiple genes at the same time. In the past decade, The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) initiatives have generated and made publicly available SCNA genomic profiles from thousands of tumor samples across multiple cancer types. Here, we present a comprehensive analysis of 853,218 SCNAs across 10,729 tumor samples belonging to 32 cancer types using TCGA data. We then discuss current models for how SCNAs likely arise during carcinogenesis and how genomic SCNA profiles can inform clinical practice. Lastly, we highlight open questions in the field of cancer-associated SCNAs.

Functional Genomic Analysis of Breast Cancer Metastasis: Implications for Diagnosis and Therapy

Simple Summary

Metastasis remains the greatest cause of fatalities in breast cancer patients world-wide. The process of metastases is highly complex, and the current research efforts in this area are still rather fragmented. The revolution of genomic profiling methods to analyze samples from human and animal models dramatically improved our understanding of breast cancer metastasis. This article summarizes the recent breakthroughs in genomic analyses of breast cancer metastasis and discusses their implications for prognostic and therapeutic applications.

Abstract

Breast cancer (BC) is one of the most diagnosed cancers worldwide and is the second cause of cancer related death in women. The most frequent cause of BC-related deaths, like many cancers, is metastasis. However, metastasis is a complicated and poorly understood process for which there is a shortage of accurate prognostic indicators and effective treatments. With the rapid and ever-evolving development and application of genomic sequencing technologies, many novel molecules were identified that play previously unappreciated and important roles in the various stages of metastasis. In this review, we summarize current advancements in the functional genomic analysis of BC metastasis and discuss about the potential prognostic and therapeutic implications from the recent genomic findings.

Heterogeneity within molecular subtypes of breast cancer

Breast cancer is the quintessential example of how molecular characterization of tumor biology guides therapeutic decisions. From the discovery of the estrogen receptor to current clinical molecular profiles to evolving single-cell analytics, the characterization and compartmentalization of breast cancer into divergent subtypes is clear. However, competing with this divergent model of breast cancer is the recognition of intratumoral heterogeneity, which acknowledges the possibility that multiple different subtypes exist within a single tumor. Intratumoral heterogeneity is driven by both intrinsic effects of the tumor cells themselves as well as extrinsic effects from the surrounding microenvironment. There is emerging evidence that these intratumoral molecular subtypes are not static; rather, plasticity between divergent subtypes is possible. Interconversion between seemingly different subtypes within a tumor drives tumor progression, metastases, and treatment resistance. Therapeutic strategies must, therefore, contend with changing phenotypes in an individual patient's tumor. Identifying targetable drivers of molecular heterogeneity may improve treatment durability and disease progression.

Amplifications of Stemness Gene Loci-New Markers for the Determination of the Need for Neoadjuvant Chemotherapy for Patients with Breast Cancer. A Prospective Study

In this prospective study, a new strategy for the prescription of neoadjuvant chemotherapy (NAC) was prospectively tested and depended on the presence of stemness gene amplifications in the tumor before treatment, which in our early studies showed a connection with metastasis. The study included 92 patients with grade IIA–IIIB luminal B breast cancer. Patients underwent a biopsy before treatment, and with the use of a CytoScan HD Array microarray (Affymetrix, Santa Clara, CA, USA), the presence of stemness gene amplifications (3q, 5p, 6p, 7q, 8q, 13q, 9p, 9q, 10p, 10q21.1, 16p, 18chr, 19p) in the tumor was determined. In group 1 (n = 41), in the presence of two or more amplifications, patients were prescribed a personalized NAC regimen. In group 2 (n = 21), if there was no amplification of stemness genes in the tumor, then patients were not prescribed NAC, and treatment began with surgery. Group 3 (n = 30) served as a historical control. The frequency of an objective response to NAC in groups 1 and 3 was 79%. Nonmetastatic survival was found in 100% of patients in group 2, who did not undergo NAC. In patients in group 1, the frequency of metastasis was 10% (4/41). At the same time, in patients in group 3, who received NAC, the rate of metastasis was 47% (14/30). The differences between group 1 and group 3 and between group 2 and group 3 were statistically significant, both by Fisher’s criterion and a log-rank test. The appointment of NAC was most feasible in patients with clones with stemness gene amplifications in the primary tumor, while in the absence of amplifications, preoperative chemotherapy led to a sharp decrease in metastasis-free survival. This strategy of NAC prescription allowed us to achieve 93% metastatic survival in patients with breast cancer.

Receptor conversion impacts outcomes of different molecular subtypes of primary breast cancer

Background

Although the conversion of clinically used breast cancer biomarkers such as estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) between primary tumors and metastatic lesions is well recognized, data on whether receptor conversion has an effect on therapy management and survival in patients with metastatic breast cancer is limited. This study aimed to investigate the clinical implications of receptor conversion throughout tumor progression.

Methods

In total, 2450 patients diagnosed with metastatic breast cancer in Tianjin Medical University Cancer Institute and Hospital were analyzed and 426 female patients with available biopsy results from both primary and metastatic sites were included in this study. We investigated the alteration of ER, PR and HER2 during breast cancer progression and evaluated the therapy management and prognostic value of receptor conversion.

Results

The conversion rates of ER, PR, and HER2 between primary tumors and metastasis were 21.1% (McNemar's test p < 0.001), 33.2% (p < 0.001), and 11.6% (p = 0.868), respectively. Evaluation of ER, PR, and HER2 status in multiple consecutive metastases revealed a change in 19.1% (p > 0.05), 23.5% (p = 0.021), and 9.8% (p > 0.05) of patients, respectively. Adjuvant therapy (chemotherapy/endocrine therapy) was related to hormone receptor conversion (p < 0.05). A statistically significant differential survival associated with hormone receptor (ER/PR) conversion (log-rank p < 0.05) was observed. In the multivariate analysis, ER conversion was an independent influence factor of survival (p < 0.05). Molecular typing conversion in primary and metastatic lesions also had a significant effect on survival (p < 0.05). We found that changing treatment based on the receptor conversion could affect clinical outcomes (p < 0.05).

Conclusions

Our findings indicated that receptor conversion during breast tumor progression had a significant effect on survival. Most importantly, our findings proved that patients with receptor conversion benefited from a change in therapy.

Genomic profile of advanced breast cancer in circulating tumour DNA

The genomics of advanced breast cancer (ABC) has been described through tumour tissue biopsy sequencing, although these approaches are limited by geographical and temporal heterogeneity. Here we use plasma circulating tumour DNA sequencing to interrogate the genomic profile of ABC in 800 patients in the plasmaMATCH trial. We demonstrate diverse subclonal resistance mutations, including enrichment of HER2 mutations in HER2 positive disease, co-occurring ESR1 and MAP kinase pathway mutations in HR + HER2- disease that associate with poor overall survival (p = 0.0092), and multiple PIK3CA mutations in HR + disease that associate with short progression free survival on fulvestrant (p = 0.0036). The fraction of cancer with a mutation, the clonal dominance of a mutation, varied between genes, and within hotspot mutations of ESR1 and PIK3CA. In ER-positive breast cancer subclonal mutations were enriched in an APOBEC mutational signature, with second hit PIK3CA mutations acquired subclonally and at sites characteristic of APOBEC mutagenesis. This study utilises circulating tumour DNA analysis in a large clinical trial to demonstrate the subclonal diversification of pre-treated advanced breast cancer, identifying distinct mutational processes in advanced ER-positive breast cancer, and novel therapeutic opportunities.

Impact of clinical targeted sequencing on endocrine responsiveness in estrogen receptor-positive, HER2-negative metastatic breast cancer

Clinical targeted sequencing allows for the selection of patients expected to have a better treatment response, and reveals mechanisms of resistance to molecular targeted therapies based on actionable gene mutations. We underwent comprehensive genomic testing with either our original in-house CLHURC system or with OncoPrime. Samples from 24 patients with estrogen receptor-positive, human epidermal growth factor receptor 2-negative metastatic breast cancer underwent targeted sequencing between 2016 and 2018. Germline and somatic gene alterations and patients' prognosis were retrospectively analyzed according to the response to endocrine therapy. All of the patients had one or more germline and/or somatic gene alterations. Four patients with primary or secondary endocrine-resistant breast cancer harbored germline pathogenic variants of BRCA1, BRCA2, or PTEN. Among somatic gene alterations, TP53, PIK3CA, AKT1, ESR1, and MYC were the most frequently mutated genes. TP53 gene mutation was more frequently observed in patients with primary endocrine resistance compared to those with secondary endocrine resistance or endocrine-responsive breast cancer. Recurrent breast cancer patients carrying TP53-mutant tumors had significantly worse overall survival compared to those with TP53-wild type tumors. Our 160-gene cancer panel will be useful to identify clinically actionable gene alterations in breast cancer in clinical practice.

Evolutionary Trajectories and Genomic Divergence in Localized Breast Cancers after Ipsilateral Breast Tumor Recurrence

Simple Summary

Ipsilateral breast tumor relapse (IBTR) occurs in 5–10% of localized breast cancers (BCs) within 10 years of incidence, despite proper treatment of the primary lesion. However, the clinical consequences of evolutionary trajectories of BC cells and their impact on IBTR remain poorly understood. Here, we conducted a longitudinal genomic analysis of 10 matched localized BC patients with IBTR. Overall, we identified the differences in homologous recombination deficiency, chromosomal instability, and somatic mutation drivers between primary and relapsed lesions. Our analyses highlighted three clonal architectures that shape by distinct mutagenic processes and subclonal diversification during relapse progression. Finally, this study provided a framework, which integrated actionable biomarkers with clonal architectures, towards improvement of future treatment decisions.

Abstract

The evolutionary trajectories that drive clinical and therapeutic consequences in localized breast cancers (BCs) with ipsilateral breast tumor relapse (IBTR) remain largely unknown. Analyses of longitudinal paired whole-exome sequencing data from 10 localized BC patients with IBTR reveal that, compared to primary breast tumors, homologous recombination (HR) deficiency, inactivation of the HR pathway, chromosomal instability, and somatic driver mutations are more frequent. Furthermore, three major models of evolution in IBTR are summarized, through which relative contributions of mutational signatures shift, and the subclonal diversity expansions are shown. Optimal treatment regimens are suggested by the clinically relevant molecular features, such as HR deficiency (20%) or specific alterations (30%) with sensitivity to available FDA-approved drugs. Finally, a rationale for the development of the therapeutic management framework is provided. This study sheds light on the complicated evolution patterns in IBTR and has significant clinical implications for future improvement of treatment decisions.

Discordance in ER, PR, HER2, and Ki-67 Expression Between Primary and Recurrent/Metastatic Lesions in Patients with Primary Early Stage Breast Cancer and the Clinical Significance: Retrospective Analysis of 75 Cases

Background: The objective was to explore the discordance in the expression of the estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and Ki-67 between primary and recurrent/metastatic lesions in patients with early stage breast cancer as well as the prognostic impact.

Method: Patients with early-stage primary breast cancer and confirmed recurrence/metastasis at Peking Union Medical College Hospital between January 2005 and August 2018 were screened. The details of discordance in each parameter between primary and recurrent/metastatic lesions and progression were recorded. Regression and survival analysis were applied to determine the association and clinical impact of the discordance.

Results: We evaluated 75 patients. The discordance rate of ER, PR, HER2, and Ki-67 expression was 9.3, 14.7, 14.7, and 21.5%, respectively. Additionally, 66.7, 11.8, 14.3, and 0% of patients with Luminal A, Luminal B, HER2, and triple-negative primary tumors presented with a different subtype for the recurrent/metastatic tumors, respectively. No statistical difference in progression-free survival was observed according to the subtype of the recurrent or metastatic breast cancer (p > 0.05). Among 69 patients for whom treatment was adjusted after recurrence or metastasis, 66 patients remained recurrence-free during the follow-up period.

Conclusion: For patients with early-stage breast cancer, the ER, PR, HER2, and Ki-67 expression profile for recurrent/metastatic tumors does not always match that of the primary tumor. After adjusting treatment according to the receptor expression in recurrent/metastatic lesions, most patients remained progression-free during the follow-up period.

Genomic evolutionary trajectory of metastatic squamous cell carcinoma of the lung

Background

The extent of inter- and intratumoral genomic heterogeneity and the clonal evolution of metastatic squamous cell carcinoma of the lung (LUSC) are poorly understood. Genomic studies of LUSC are challenged by their low tumor cell content. We sought to define the genomic landscape and evolutionary trajectories of metastatic LUSC combining nuclei-flow sorting and whole exome sequencing.

Methods

Five patients with primary LUSC and six matched metastases were investigated. Tumor nuclei were sorted based on ploidy and expression of cytokeratin to enrich for tumor cells for whole exome sequencing.

Results

Flow-sorting increased the mean tumor purity from 26% (range, 12–50%) to 73% (range, 42–93%). Overall, primary LUSCs and their matched metastases shared a median of 79% (range, 67–85%) of copy number aberrations (CNAs) and 74% (range, 65–94%) of non-synonymous mutations, including in tumor suppressor genes such as TP53. Furthermore, the ploidy of the tumors remained unchanged between primary and metastasis in 4/5 patients over time. We found differences in the mutational signatures of shared mutations compared to the private mutations in the primary or metastasis.

Conclusions

Our results demonstrate a close genomic relationship between primary LUSCs and their matched metastases, suggesting late dissemination of the metastases from the primary tumors during tumor evolution.

Molecular features of untreated breast cancer and initial metastatic event inform clinical decision-making and predict outcome: long-term results of ESOPE, a single-arm prospective multicenter study

Background

Prognosis evaluation of advanced breast cancer and therapeutic strategy are mostly based on clinical features of advanced disease and molecular profiling of the primary tumor. Very few studies have evaluated the impact of metastatic subtyping during the initial metastatic event in a prospective study. The genomic landscape of metastatic breast cancer has mostly been described in very advanced, pretreated disease, limiting the findings transferability to clinical use.

Methods

We developed a multicenter, single-arm, prospective clinical trial in order to address these issues. Between November 2010 and September 2013, 123 eligible patients were included. Patients at the first, untreated metastatic event were eligible. All matched primary tumors and metastatic samples were centrally reviewed for pathological typing. Targeted and whole-exome sequencing was applied to matched pairs of frozen tissue. A multivariate overall survival analysis was performed (median follow-up 64 months).

Results

Per central review in 84 patients (out of 130), we show that luminal A breast tumors are more prone to subtype switching. By combining targeted sequencing of a 91 gene panel (n = 67) and whole-exome sequencing (n = 30), a slight excess of mutations is observed in the metastases. Luminal A breast cancer has the most heterogeneous mutational profile and the highest number of mutational signatures, when comparing primary tumor and the matched metastatic tissue. Tumors with a subtype change have more mutations that are private. The metastasis-specific mutation load is significantly higher in late than in de novo metastases. The most frequently mutated genes were TP53 and PIK3CA. The most frequent metastasis-specific druggable genes were PIK3CA, PTEN, KDR, ALK, CDKN2A, NOTCH4, POLE, SETD2, SF3B1, and TSC2. Long-term outcome is driven by a combination of tumor load and metastasis biology.

Conclusions

Profiling of the first, untreated, metastatic event of breast cancer reveals a profound heterogeneity mostly in luminal A tumors and in late metastases. Based on this profiling, we can derive information relevant to prognosis and therapeutic intervention, which support current guidelines recommending a biopsy at the first metastatic relapse.

Trial registration

The trial was registered at ClinicalTrials.gov (NCT01956552).

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-021-00862-6.

Prognosis and Genomic Landscape of Liver Metastasis in Patients With Breast Cancer

Objective

The prognosis of breast cancer liver metastasis (BCLM) is poor, and its molecular mechanism is unclear. We aimed to determine the factors that affect the prognosis of patients with BCLM and investigate the genomic landscape of liver metastasis (LM).

Methods

We described the prognosis of patients with BCLM and focused on prognosis prediction for these patients based on clinicopathological factors. Nomogram models were constructed for progression-free survival (PFS) and overall survival (OS) by using a cohort of 231 patients with BCLM who underwent treatment at Shandong Cancer Hospital and Institute (SCHI). We explored the molecular mechanism of LM and constructed driver genes, mutation signatures by using a targeted sequencing dataset of 217 samples of LM and 479 unpaired samples of primary breast cancer (pBC) from Memorial Sloan Kettering Cancer Center (MSKCC).

Results

The median follow-up time for 231 patients with BCLM in the SCHI cohort was 46 months. The cumulative incidence of LM at 1, 2, and 5 years was 17.5%, 45.0%, and 86.8%, respectively. The median PFS and OS were 7 months (95% CI, 6-8) and 22 months (95% CI, 19-25), respectively. The independent factors that increased the progression risk of patients with LM were Karnofsky performance status (KPS) ≤ 80, TNBC subtype, grade III, increasing trend of CA153, and disease-free interval (DFS) ≤ 1 year. Simultaneously, the independent factors that increased the mortality risk of patients with LM were Ki-67 ≥ 30%, grade III, increasing trend of CA153, pain with initial LM, diabetes, and DFI ≤ 1 year. In the MSKCC dataset, the LM driver genes were ESR1, AKT1, ERBB2, and FGFR4, and LM matched three prominent mutation signatures: APOBEC cytidine deaminase, ultraviolet exposure, and defective DNA mismatch repair.

Conclusion

This study systematically describes the survival prognosis and characteristics of LM from the clinicopathological factors to the genetic level. These results not only enable clinicians to assess the risk of disease progression in patients with BCLM to optimize treatment options, but also help us better understand the underlying mechanisms of tumor metastasis and evolution and provide new therapeutic targets with potential benefits for drug-resistant patients.

Molecular Heterogeneity and Evolution in Breast Cancer

Breast cancer comprises a heterogeneous group of tumor subtypes, whether defined by immunohistochemistry of key proteins, RNA expression profiles, or genetic alterations, and each of these subtypes may benefit from a distinct treatment approach. However, there can be striking heterogeneity within tumors, which may pose challenges to the development of personalized approaches to therapy. Intratumor heterogeneity can be divided into three main categories: genetic, phenotypic, and microenvironmental. Here, we review technologies to interrogate these three categories of heterogeneity in patient samples, as well as the current state of understanding of these categories in breast cancer, from cell to cell, across different regions of the same tumor mass, across treatment, and across metastasis. Efforts to characterize tumor heterogeneity longitudinally will be crucial to the development of personalized oncology for breast cancer.

DNA damage response as a prognostic indicator in metastatic breast cancer via mutational analysis

Background

High tumor heterogeneity contributes to breast cancer recurrence and metastasis. However, the lack of indicators to serve as precise and reliable means of predicting breast cancer prognosis has yet to be addressed. This study aims to reveal the prognostic relevance of mutations in metastatic breast cancer (MBC) by large-scale circulating tumor DNA (ctDNA) analysis in China.

Methods

We performed ctDNA panel-captured sequencing of 958 blood samples from MBC patients including 494 hormone receptor (HR)-positive cases, 130 human epidermal growth factor receptor 2-positive cases, and 177 triple-negative breast cancer (TNBC) cases. The somatic mutations and potential targets were assessed. Progression-free survival (PFS) was analyzed using the Kaplan-Meier method.

Results

In 801 of the 958 MBC blood samples, 663 mutated genes and 5,829 nonsynonymous alterations were identified. Mutated genes of the highest frequency were tumor protein p53 (TP53, 54%), phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha (PIK3CA, 41%), estrogen receptor 1 (ESR1, 12%), myeloid/lymphoid or mixed-lineage leukemia protein 3 (MLL3, 11%), DNA (cytosine-5)-methyltransferase 3A (DNMT3A, 10%), erb-b2 receptor tyrosine kinase 2 (ERBB2, 10%), GATA binding protein 3 (GATA3, 8%), FAT atypical cadherin 1 (FAT1, 7%), phosphatase and tensin homolog (PTEN, 6%), and mitogen-activated protein kinase kinase kinase 1 (MAP3K1, 6%). Enriched mutations and driver genes in MBC varied across stages and in multiple subtypes. Moreover, TP53, ERBB2, or coexisting TP53/PIK3CA mutations in MBC were remarkably related with shorter PFS. Mutated DNA damage response (DDR) genes were significantly associated with tumor mutation burden and mutant-allele tumor heterogeneity score, as well as with worse clinical outcome.

Conclusions

Our findings indicate that the mutations of TP53, PIK3CA, ERBB2, and in particular, DDR genes, in MBC might be relevant indicators of unfavorable prognosis in MBC.

Pathway-Based Drug-Repurposing Schemes in Cancer: The Role of Translational Bioinformatics

Cancer is a set of complex pathologies that has been recognized as a major public health problem worldwide for decades. A myriad of therapeutic strategies is indeed available. However, the wide variability in tumor physiology, response to therapy, added to multi-drug resistance poses enormous challenges in clinical oncology. The last years have witnessed a fast-paced development of novel experimental and translational approaches to therapeutics, that supplemented with computational and theoretical advances are opening promising avenues to cope with cancer defiances. At the core of these advances, there is a strong conceptual shift from gene-centric emphasis on driver mutations in specific oncogenes and tumor suppressors-let us call that the silver bullet approach to cancer therapeutics-to a systemic, semi-mechanistic approach based on pathway perturbations and global molecular and physiological regulatory patterns-we will call this the shrapnel approach. The silver bullet approach is still the best one to follow when clonal mutations in driver genes are present in the patient, and when there are targeted therapies to tackle those. Unfortunately, due to the heterogeneous nature of tumors this is not the common case. The wide molecular variability in the mutational level often is reduced to a much smaller set of pathway-based dysfunctions as evidenced by the well-known hallmarks of cancer. In such cases "shrapnel gunshots" may become more effective than "silver bullets". Here, we will briefly present both approaches and will abound on the discussion on the state of the art of pathway-based therapeutic designs from a translational bioinformatics and computational oncology perspective. Further development of these approaches depends on building collaborative, multidisciplinary teams to resort to the expertise of clinical oncologists, oncological surgeons, and molecular oncologists, but also of cancer cell biologists and pharmacologists, as well as bioinformaticians, computational biologists and data scientists. These teams will be capable of engaging on a cycle of analyzing high-throughput experiments, mining databases, researching on clinical data, validating the findings, and improving clinical outcomes for the benefits of the oncological patients.

Deciphering the clonal relationship between glandular and squamous components in adenosquamous carcinoma of the lung using whole exome sequencing

Adenosquamous carcinoma of the lung (ASC) is a rare subtype of non-small cell lung cancer, consisting of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) components. ASC shows morphological characteristics of classic LUAD and LUSC but behaves more aggressively. Although ASC can serve as a model of lung cancer heterogeneity and transdifferentiation, its genomic background remains poorly understood. In this study, we sought to explore the genomic landscape of macrodissected LUAD and LUSC components of three ASC using whole exome sequencing (WES). Identified truncal mutations included the pan-cancer tumor-suppressor gene TP53 but also EGFR, BRAF, and MET, which are characteristic for LUAD but uncommon in LUSC. No truncal mutation of classical LUSC driver mutations were found. Both components showed unique driver mutations that did not overlap between the three ASC. Mutational signatures of truncal mutations differed from those of the branch mutations in their descendants LUAD and LUSC. Most common signatures were related to aging (1, 5) and smoking (4). Truncal chromosomal copy number aberrations shared by all three ASC included losses of 3p, 15q and 19p, and an amplified region in 5p. Furthermore, we detected loss of STK11 and SOX2 amplification in ASC, which has previously been shown to drive transdifferentiation from LUAD to LUSC in preclinical mouse models. Conclusively, this is the first study using WES to elucidate the clonal evolution of ASC. It provides strong evidence that the LUAD and LUSC components of ASC share a common origin and that the LUAD component appears to transform to LUSC.

Clonal Evolution and Timing of Metastatic Colorectal Cancer

Colorectal cancer (CRC) is the third most frequently diagnosed cancer worldwide, where ~50% of patients develop metastasis, despite current improved management. Genomic characterisation of metastatic CRC, and elucidating the effects of therapy on the metastatic process, are essential to help guide precision medicine. Multi-region whole-exome sequencing was performed on 191 sampled tumour regions of patient-matched therapy-naïve and treated CRC primary tumours (n = 92 tumour regions) and metastases (n = 99 tumour regions), in 30 patients. Somatic variants were analysed to define the origin, composition, and timing of seeding in the metastatic progression of therapy-naïve and treated metastatic CRC. High concordance, with few genomic differences, was observed between primary CRC and metastases. Most cases supported a late dissemination model, via either monoclonal or polyclonal seeding. Polyclonal seeding appeared more common in therapy-naïve metastases than in treated metastases. Whereby, treatment prompted for the selection of distinct resistant clones, through monoclonal seeding to distant metastatic sites. Overall, this study reinforces the importance of early clinical detection and surgical excision of the CRC tumour, whilst further highlighting the clinical challenges for metastatic CRC with increased intratumour heterogeneity (either due to early dissemination or polyclonal metastatic spread) and the underlying risk of future therapeutic resistance in treated patients.

Genomic landscape of metastatic breast cancer identifies preferentially dysregulated pathways and targets

Nearly all breast cancer deaths result from metastatic disease. Despite this, the genomic events that drive metastatic recurrence are poorly understood. We performed whole-exome and shallow whole-genome sequencing to identify genes and pathways preferentially mutated or copy-number altered in metastases compared with the paired primary tumors from which they arose. Seven genes were preferentially mutated in metastases - MYLK, PEAK1, SLC2A4RG, EVC2, XIRP2, PALB2, and ESR1 - 5 of which are not significantly mutated in any type of human primary cancer. Four regions were preferentially copy-number altered: loss of STK11 and CDKN2A/B, as well as gain of PTK6 and the membrane-bound progesterone receptor, PAQR8. PAQR8 gain was mutually exclusive with mutations in the nuclear estrogen and progesterone receptors, suggesting a role in treatment resistance. Several pathways were preferentially mutated or altered in metastases, including mTOR, CDK/RB, cAMP/PKA, WNT, HKMT, and focal adhesion. Immunohistochemical analyses revealed that metastases preferentially inactivate pRB, upregulate the mTORC1 and WNT signaling pathways, and exhibit nuclear localization of activated PKA. Our findings identify multiple therapeutic targets in metastatic recurrence that are not significantly mutated in primary cancers, implicate membrane progesterone signaling and nuclear PKA in metastatic recurrence, and provide genomic bases for the efficacy of mTORC1, CDK4/6, and PARP inhibitors in metastatic breast cancer.

Genomic profiling of primary and recurrent adult granulosa cell tumors of the ovary

Adult-type granulosa cell tumor (aGCT) is a rare malignant ovarian sex cord-stromal tumor, harboring recurrent FOXL2 c.C402G/p.C134W hotspot mutations in 97% of cases. These tumors are considered to have a favorable prognosis, however aGCTs have a tendency for local spread and late recurrences, which are associated with poor survival rates. We sought to determine the genetic alterations associated with aGCT disease progression. We subjected primary non-recurrent aGCTs (n = 7), primary aGCTs that subsequently recurred (n = 9) and their matched recurrences (n = 9), and aGCT recurrences without matched primary tumors (n = 10) to targeted massively parallel sequencing of ≥410 cancer-related genes. In addition, three primary non-recurrent aGCTs and nine aGCT recurrences were subjected to FOXL2 and TERT promoter Sanger sequencing analysis. All aGCTs harbored the FOXL2 C134W hotspot mutation. TERT promoter mutations were found to be significantly more frequent in recurrent (18/28, 64%) than primary aGCTs (5/19, 26%, p = 0.017). In addition, mutations affecting TP53, MED12, and TET2 were restricted to aGCT recurrences. Pathway annotation of altered genes demonstrated that aGCT recurrences displayed an enrichment for genetic alterations affecting cell cycle pathway-related genes. Analysis of paired primary and recurrent aGCTs revealed that TERT promoter mutations were either present in both primary tumors and matched recurrences or were restricted to the recurrence and absent in the respective primary aGCT. Clonal composition analysis of these paired samples further revealed that aGCTs display intra-tumor genetic heterogeneity and harbor multiple clones at diagnosis and relapse. We observed that in a subset of cases, recurrences acquired additional genetic alterations not present in primary aGCTs, including TERT, MED12, and TP53 mutations and CDKN2A/B homozygous deletions. Albeit harboring relatively simple genomes, our data provide evidence to suggest that aGCTs are genetically heterogeneous tumors and that TERT promoter mutations and/or genetic alterations affecting other cell cycle-related genes may be associated with disease progression and recurrences.

Microvesicles in Cancer: Small Size, Large Potential

Extracellular vesicles (EV) are secreted by all cell types in a tumor and its microenvironment (TME), playing an essential role in intercellular communication and the establishment of a TME favorable for tumor invasion and metastasis. They encompass a variety of vesicle populations, among them the well-known endosomal-derived small exosomes (Exo), but also larger vesicles (diameter > 100 nm) that are shed directly from the plasma membrane, the so-called microvesicles (MV). Increasing evidence suggests that MV, although biologically different, share the tumor-promoting features of Exo in the TME. Due to their larger size, they can be readily harvested from patients' blood and characterized by routine methods such as conventional flow cytometry, exploiting the plethora of molecules expressed on their surface. In this review, we summarize the current knowledge about the biology and the composition of MV, as well as their role within the TME. We highlight not only the challenges and potential of MV as novel biomarkers for cancer, but also discuss their possible use for therapeutic intervention.

A machine learning model that classifies breast cancer pathologic complete response on MRI post-neoadjuvant chemotherapy

Background

For breast cancer patients undergoing neoadjuvant chemotherapy (NAC), pathologic complete response (pCR; no invasive or in situ) cannot be assessed non-invasively so all patients undergo surgery. The aim of our study was to develop and validate a radiomics classifier that classifies breast cancer pCR post-NAC on MRI prior to surgery.

Methods

This retrospective study included women treated with NAC for breast cancer from 2014 to 2016 with (1) pre- and post-NAC breast MRI and (2) post-NAC surgical pathology report assessing response. Automated radiomics analysis of pre- and post-NAC breast MRI involved image segmentation, radiomics feature extraction, feature pre-filtering, and classifier building through recursive feature elimination random forest (RFE-RF) machine learning. The RFE-RF classifier was trained with nested five-fold cross-validation using (a) radiomics only (model 1) and (b) radiomics and molecular subtype (model 2). Class imbalance was addressed using the synthetic minority oversampling technique.

Results

Two hundred seventy-three women with 278 invasive breast cancers were included; the training set consisted of 222 cancers (61 pCR, 161 no-pCR; mean age 51.8 years, SD 11.8), and the independent test set consisted of 56 cancers (13 pCR, 43 no-pCR; mean age 51.3 years, SD 11.8). There was no significant difference in pCR or molecular subtype between the training and test sets. Model 1 achieved a cross-validation AUROC of 0.72 (95% CI 0.64, 0.79) and a similarly accurate (P = 0.1) AUROC of 0.83 (95% CI 0.71, 0.94) in both the training and test sets. Model 2 achieved a cross-validation AUROC of 0.80 (95% CI 0.72, 0.87) and a similar (P = 0.9) AUROC of 0.78 (95% CI 0.62, 0.94) in both the training and test sets.

Conclusions

This study validated a radiomics classifier combining radiomics with molecular subtypes that accurately classifies pCR on MRI post-NAC.

Genetic alterations and their association with clinicopathologic characteristics in advanced breast carcinomas: focusing on clinically actionable genetic alterations

Breast carcinomas (BCs) are genetically heterogeneous and associated with numerous mutations which can be used to predict outcomes and initiate targeted therapies. We investigated clinicopathologic characteristics associated with gene mutations detected using the FoundationOne CDx assay in a cohort of 223 clinically advanced BCs (66 locally recurrent and 157 metastatic) from our institution. One hundred fifty unique mutations were identified (total 1008) in the cohort, with the most prevalent (>10%) including TP53 (53.8%), PIK3CA (35%), MYC (22%), CCND1 (19.7%), FGF19 (19.7%), FGF4 (16.6%), FGF3 (16.1%), ZNF703 (14.8%), ESR1 (13.9%), FGFR1 (13.5%), PTEN (12.1%), and CDH1 (10.8%). ERBB2 genetic alteration was most common in human epidermal growth factor receptor 2 (HER2)-positive BCs, and GATA3 and ESR1 mutations were only identified in hormone receptor-positive BC. Mutations enriched in triple-negative BCs (TNBCs) included TP53, PTEN, RB1, and CDKN2A/B. CDH1 mutation was predominantly found in lobular carcinomas, and PIK3CA mutation was also enriched. Mutations enriched in metaplastic carcinomas with heterologous mesenchymal differentiation included TP53, PTEN, MCL1, CDKN2A/B, and NOTCH2. An increase in mutations of CCND1, FGF19, FGF4, FGF3, ESR1, and EMSY was identified in metastatic BCs compared with locally recurrent BCs. Overall, PIK3CA was the most frequent clinically actionable genetic alteration (35%), followed by MYC (22%), CCND1 (19.7%), and FGF3/FGF4/FGFR1 (16%). In conclusion, our study provides genetic insight into the biology of advanced BCs and summarizes their most frequent clinically actionable genetic alterations, generating useful genomic information for potential improvement of patient management.