Tumor intrinsic subtype is reflected in cancer-adjacent tissue

Single-cell transcriptomic landscape and the microenvironment of normal adjacent tissues in hypopharyngeal carcinoma

BACKGROUND

The cellular origin of hypopharyngeal diseases is crucial for further diagnosis and treatment, and the microenvironment in tissues may also be associated with specific cell types at the same time. Normal adjacent tissues (NATs) of hypopharyngeal carcinoma differ from non-tumor-bearing tissues, and can influenced by the tumor. However, the heterogeneity in kinds of disease samples remains little known, and the transcriptomic profile about biological information associated with disease occurrence and clinical outcome contained in it has yet to be fully evaluated. For these reasons, we should quickly investigate the taxonomic and transcriptomic information of NATs in human hypopharynx.

RESULTS

Single-cell suspensions of normal adjacent tissues (NATs) of hypopharyngeal carcinoma were obtained and single-cell RNA sequencing (scRNA-seq) was performed. We present scRNA-seq data from 39,315 high-quality cells in the hypopharyngeal from five human donors, nine clusters of normal adjacent human hypopharyngeal cells were presented, including epithelial cells, endothelial cells (ECs), mononuclear phagocyte system cells (MPs), fibroblasts, T cells, plasma cells, B cells, mural cells and mast cells. Nonimmune components in the microenvironment, including epithelial cells, endothelial cells, fibroblasts and the subpopulations of them were performed.

CONCLUSIONS

Our data provide a solid basis for the study of single-cell landscape in human normal adjacent hypopharyngeal tissues biology and related diseases.

AI-powered interpretable imaging phenotypes noninvasively characterize tumor microenvironment associated with diverse molecular signatures and survival in breast cancer

BACKGROUND AND OBJECTIVES

Tumor microenvironment (TME) is a determining factor in decision-making and personalized treatment for breast cancer, which is highly intra-tumor heterogeneous (ITH). However, the noninvasive imaging phenotypes of TME are poorly understood, even invasive genotypes have been largely known in breast cancer.

METHODS

Here, we develop an artificial intelligence (AI)-driven approach for noninvasively characterizing TME by integrating the predictive power of deep learning with the explainability of human-interpretable imaging phenotypes (IMPs) derived from 4D dynamic imaging (DCE-MRI) of 342 breast tumors linked to genomic and clinical data, which connect cancer phenotypes to genotypes. An unsupervised dual-attention deep graph clustering model (DGCLM) is developed to divide bulk tumor into multiple spatially segregated and phenotypically consistent subclusters. The IMPs ranging from spatial heterogeneity to kinetic heterogeneity are leveraged to capture architecture, interaction, and proximity between intratumoral subclusters.

RESULTS

We demonstrate that our IMPs correlate with well-known markers of TME and also can predict distinct molecular signatures, including expression of hormone receptor, epithelial growth factor receptor and immune checkpoint proteins, with the performance of accuracy, reliability and transparency superior to recent state-of-the-art radiomics and 'black-box' deep learning methods. Moreover, prognostic value is confirmed by survival analysis accounting for IMPs.

CONCLUSIONS

Our approach provides an interpretable, quantitative, and comprehensive perspective to characterize TME in a noninvasive and clinically relevant manner.

A snapshot of miRNAs in oral squamous cell carcinoma: Difference between cancer cells and corresponding normal cells

Oral squamous cell carcinoma (OSCC) constitutes the most aggressive tumors of the oral cavity and is one of the leading causes of cancer mortality worldwide. Although recent clinical treatment strategies have improved the survival rate, the outcome of OSCC patients still remains dismal because of the lack of efficient diagnostic and treatment tools. As one of the main actors of OSCC scenario, microRNAs (miRNAs) are involved in triggering, progression and metastasis through the regulation of various cancer-related signaling pathways. Identification followed by precise study of the biology and mechanism of action of miRNAs will greatly help to provide valuable insights regarding OSCC development and can be considered as an anti-OSCC target. In the current review, we have provided a focused summary of the latest published papers on the role of miRNAs in apoptosis, cell cycle, proliferation, EMT and metastasis of OSCC as well as the role of long noncoding RNAs in the modulation of miRNAs in OSCC.

Proteomics of adjacent-to-tumor samples uncovers clinically relevant biological events in hepatocellular carcinoma

Normal adjacent tissues (NATs) of hepatocellular carcinoma (HCC) differ from healthy liver tissues and their heterogeneity may contain biological information associated with disease occurrence and clinical outcome that has yet to be fully evaluated at the proteomic level. This study provides a detailed description of the heterogeneity of NATs and the differences between NATs and healthy livers and revealed that molecular features of tumor subgroups in HCC were partially reflected in their respective NATs. Proteomic data classified HCC NATs into two subtypes (Subtypes 1 and 2), and Subtype 2 was associated with poor prognosis and high-risk recurrence. The pathway and immune features of these two subtypes were characterized. Proteomic differences between the two NAT subtypes and healthy liver tissues were further investigated using data-independent acquisition mass spectrometry, revealing the early molecular alterations associated with the progression from healthy livers to NATs. This study provides a high-quality resource for HCC researchers and clinicians and may significantly expand the knowledge of tumor NATs to eventually benefit clinical practice.

Therapeutic Potential of Tumor Metabolic Reprogramming in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer, with clinical features of high metastatic potential, susceptibility to relapse, and poor prognosis. TNBC lacks the expression of the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). It is characterized by genomic and transcriptional heterogeneity and a tumor microenvironment (TME) with the presence of high levels of stromal tumor-infiltrating lymphocytes (TILs), immunogenicity, and an important immunosuppressive landscape. Recent evidence suggests that metabolic changes in the TME play a key role in molding tumor development by impacting the stromal and immune cell fractions, TME composition, and activation. Hence, a complex inter-talk between metabolic and TME signaling in TNBC exists, highlighting the possibility of uncovering and investigating novel therapeutic targets. A better understanding of the interaction between the TME and tumor cells, and the underlying molecular mechanisms of cell-cell communication signaling, may uncover additional targets for better therapeutic strategies in TNBC treatment. In this review, we aim to discuss the mechanisms in tumor metabolic reprogramming, linking these changes to potential targetable molecular mechanisms to generate new, physical science-inspired clinical translational insights for the cure of TNBC.

Transcriptomes of the tumor-adjacent normal tissues are more informative than tumors in predicting recurrence in colorectal cancer patients

BACKGROUND

Previous investigations of transcriptomic signatures of cancer patient survival and post-therapy relapse have focused on tumor tissue. In contrast, here we show that in colorectal cancer (CRC) transcriptomes derived from normal tissues adjacent to tumors (NATs) are better predictors of relapse.

RESULTS

Using the transcriptomes of paired tumor and NAT specimens from 80 Korean CRC patients retrospectively determined to be in recurrence or nonrecurrence states, we found that, when comparing recurrent with nonrecurrent samples, NATs exhibit a greater number of differentially expressed genes (DEGs) than tumors. Training two prognostic elastic net-based machine learning models-NAT-based and tumor-based in our Samsung Medical Center (SMC) cohort, we found that NAT-based model performed better in predicting the survival when the model was applied to the tumor-derived transcriptomes of an independent cohort of 450 COAD patients in TCGA. Furthermore, compositions of tumor-infiltrating immune cells in NATs were found to have better prognostic capability than in tumors. We also confirmed through Cox regression analysis that in both SMC-CRC as well as in TCGA-COAD cohorts, a greater proportion of genes exhibited significant hazard ratio when NAT-derived transcriptome was used compared to when tumor-derived transcriptome was used.

CONCLUSIONS

Taken together, our results strongly suggest that NAT-derived transcriptomes and immune cell composition of CRC are better predictors of patient survival and tumor recurrence than the primary tumor.

In Vitro Evidence of Differential Immunoregulatory Response between MDA-MB-231 and BT-474 Breast Cancer Cells Induced by Bone Marrow-Derived Mesenchymal Stromal Cells Conditioned Medium

Inside tumors, cancer cells display several mechanisms to create an immunosuppressive environment. On the other hand, by migration processes, mesenchymal stromal cells (MSCs) can be recruited by different cancer tumor types from tissues as distant as bone marrow and contribute to tumor pathogenesis. However, the impact of the immunoregulatory role of MSCs associated with the aggressiveness of breast cancer cells by soluble molecules has not been fully elucidated. Therefore, this in vitro work aimed to study the effect of the conditioned medium of human bone marrow-derived-MSCs (hBM-MSC-cm) on the immunoregulatory capability of MDA-MB-231 and BT-474 breast cancer cells. The hBM-MSC-cm on MDA-MB-231 cells induced the overexpression of TGF-β, IDO, and IL-10 genes. Additionally, immunoregulation assays of mononuclear cells (MNCs) in co-culture with MDA-MB-231 and hBM-MSC-cm decreased lymphocyte proliferation, and increased proteins IL-10, TGF-β, and IDO while also reducing TNF levels, shooting the proportion of regulatory T cells. Conversely, the hBM-MSC-cm did not affect the immunomodulatory capacity of BT-474 cells. Thus, a differential immunoregulatory effect was observed between both representative breast cancer cell lines from different origins. Thus, understanding the immune response in a broader tumor context could help to design therapeutic strategies based on the aggressive behavior of tumor cells.

Endometrial Cancer-Adjacent Tissues Express Higher Levels of Cancer-Promoting Genes than the Matched Tumors

Molecular alterations in tumor-adjacent tissues have recently been recognized in some types of cancer. This phenomenon has not been studied in endometrial cancer. We aimed to analyze the expression of genes associated with cancer progression and metabolism in primary endometrial cancer samples and the matched tumor-adjacent tissues and in the samples of endometria from cancer-free patients with uterine leiomyomas. Paired samples of tumor-adjacent tissues and primary tumors from 49 patients with endometrial cancer (EC), samples of endometrium from 25 patients with leiomyomas of the uterus, and 4 endometrial cancer cell lines were examined by the RT-qPCR, for MYC, NR5A2, CXCR2, HMGA2, LIN28A, OCT4A, OCT4B, OCT4B1, TWIST1, STK11, SNAI1, and miR-205-5p expression. The expression levels of MYC, NR5A2, SNAI1, TWIST1, and STK11 were significantly higher in tumor-adjacent tissues than in the matched EC samples, and this difference was not influenced by the content of cancer cells in cancer-adjacent tissues. The expression of MYC, NR5A2, and SNAI1 was also higher in EC-adjacent tissues than in samples from cancer-free patients. In addition, the expression of MYC and CXCR2 in the tumor related to non-endometrioid adenocarcinoma and reduced the risk of recurrence, respectively, and higher NR5A2 expression in tumor-adjacent tissue increased the risk of death. In conclusion, tissues proximal to EC present higher levels of some cancer-promoting genes than the matched tumors. Malignant tumor-adjacent tissues carry a diagnostic potential and emerge as new promising target of anticancer therapy.

A deep learning model to classify neoplastic state and tissue origin from transcriptomic data

Application of deep learning methods to transcriptomic data has the potential to enhance the accuracy and efficiency of tissue classification and cell state identification. Herein, we developed a multitask deep learning model for tissue classification combining publicly available whole transcriptomic (RNA-seq) datasets of non-neoplastic, neoplastic and peri-neoplastic tissue to classify disease state, tissue origin and neoplastic subclass. RNA-seq data from a total of 10,116 patient samples processed through a common pipeline were used for model training and validation. The model achieved 99% accuracy for disease state classification (ROC-AUC of 0.98) and 97% accuracy for tissue origin (ROC-AUC of 0.99). Moreover, the model achieved an accuracy of 92% (ROC-AUC 0.95) for neoplastic subclassification. This is the first multitask deep learning algorithm developed for tissue classification employing a uniform pipeline analysis of transcriptomic data with multiple tissue classifiers. This model serves as a framework for incorporating large transcriptomic datasets across conditions to facilitate clinical diagnosis and cell-based treatment strategies.

Field cancerization in breast cancer

Breast cancer affects one in seven women worldwide during their lifetime. Widespread mammographic screening programs and education campaigns allow for early detection of the disease, often during its asymptomatic phase. Current practice in treatment and recurrence monitoring is based primarily on pathological evaluations but can also encompass genomic evaluations, both of which focus on the primary tumor. Although breast cancer is one of the most studied cancers, patients still recur at a rate of up to 15% within the first 10 years post‐surgery. Local recurrence was originally attributed to tumor cells contaminating histologically normal (HN) tissues beyond the surgical margin, but advances in technology have allowed for the identification of distinct aberrations that exist in the peri‐tumoral tissues themselves. One leading theory to explain this phenomenon is the field cancerization theory. Under this hypothesis, tumors arise from a field of molecularly altered cells that create a permissive environment for malignant evolution, which can occur with or without morphological changes. The traditional histopathology paradigm dictates that molecular alterations are reflected in the tissue phenotype. However, the spectrum of inter‐patient variability of normal breast tissue may obfuscate recognition of a cancerized field during routine diagnostics. In this review, we explore the concept of field cancerization focusing on HN peri‐tumoral tissues: we present the pathological and molecular features of field cancerization within these tissues and discuss how the use of peri‐tumoral tissues can affect research. Our observations suggest that pathological and molecular evaluations could be used synergistically to assess risk and guide the therapeutic management of patients. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Proteomic Identification of a Gastric Tumor ECM Signature Associated With Cancer Progression

The extracellular matrix (ECM) plays an undisputable role in tissue homeostasis and its deregulation leads to altered mechanical and biochemical cues that impact cancer development and progression. Herein, we undertook a novel approach to address the role of gastric ECM in tumorigenesis, which remained largely unexplored. By combining decellularization techniques with a high-throughput quantitative proteomics approach, we have performed an extensive characterization of human gastric mucosa, uncovering its composition and distribution among tumor, normal adjacent and normal distant mucosa. Our results revealed a common ECM signature composed of 142 proteins and indicated that gastric carcinogenesis encompasses ECM remodeling through alterations in the abundance of 24 components, mainly basement membrane proteins. Indeed, we could only identify one de novo tumor-specific protein, the collagen alpha-1(X) chain (COL10A1). Functional analysis of the data demonstrated that gastric ECM remodeling favors tumor progression by activating ECM receptors and cellular processes involved in angiogenesis and cell-extrinsic metabolic regulation. By analyzing mRNA expression in an independent GC cohort available at the TGCA, we validated the expression profile of 12 differentially expressed ECM proteins. Importantly, the expression of COL1A2, LOX and LTBP2 significantly correlated with high tumor stage, with LOX and LTBP2 further impacting patient overall survival. These findings contribute for a better understanding of GC biology and highlight the role of core ECM components in gastric carcinogenesis and their clinical relevance as biomarkers of disease prognosis.

The DNA damage repair landscape in Black women with breast cancer

BACKGROUND

Estrogen receptor positive (ER+) breast cancer is one of the most commonly diagnosed malignancies in women irrespective of their race or ethnicity. While Black women with ER+ breast cancer are 42% more likely to die of their disease than White women, molecular mechanisms underlying this disparate outcome are understudied. Recent studies identify DNA damage repair (DDR) genes as a new class of endocrine therapy resistance driver that contributes to poor survival among ER+ breast cancer patients. Here, we systematically analyze DDR regulation in the tumors and normal breast of Black women and its impact on survival outcome.

METHOD

Mutation and up/downregulation of 104 DDR genes in breast tumor and normal samples from Black patients relative to White counterparts was assessed. For DDR genes that were differently regulated in the tumor samples from Black women in multiple datasets associations with survival outcome were tested.

RESULTS

Overall, Black patient tumors upregulate or downregulate RNA levels of a wide array of single strand break repair (SSBR) genes relative to their white counterparts and uniformly upregulate double strand break repair (DSBR) genes. This DSBR upregulation was also detectable in samples of normal breast tissue from Black women. Eight candidate DDR genes were reproducibly differently regulated in tumors from Black women and associated with poor survival. A unique DDR signature comprised of simultaneous upregulation of homologous recombination gene expression and downregulation of SSBR genes was enriched in Black patients. This signature associated with cell cycle dysregulation (p < 0.001), a hallmark of endocrine therapy resistance, and concordantly, with significantly worse survival outcomes in all datasets analyzed (hazard ratio of 9.5, p < 0.001).

CONCLUSION

These results constitute the first systematic analysis of DDR regulation in Black women and provide strong rationale for refining biomarker profiles to ensure precision medicine for underserved populations.

The Characteristics of Tumor Microenvironment in Triple Negative Breast Cancer

Triple-negative breast cancer (TNBC) is a special subtype of breast cancer, accounting for 10-20% of breast cancers with high intrinsic heterogeneity. Its unique immune microenvironment, including high expression of vascular endothelial growth factors, tumor infiltrating lymphocytes (TILs), tumor-associated macrophages (TAMs), and other molecules that promote the growth and migration of tumor cells, has been shown to play a dual role in the occurrence, growth, and metastasis of TNBC. Understanding the TNBC microenvironment is of great significance for the prognosis and treatment of TNBC. In this article, we describe the composition and function of immune cells in the TNBC microenvironment and summarize the major cytokine growth factors and chemokines in the TNBC microenvironment. Finally, we discuss the progress of TNBC, cytokine-induced killer cell therapy, and immune checkpoint therapy.

Chemosensitivity analysis and study of gene resistance on tumors and cancer stem cell isolates from patients with colorectal cancer

Colorectal cancer (CRC) is one of the main causes of mortality. Recent studies suggest that cancer stem cells (CSCs) can survive after chemotherapy and promote tumor invasiveness and aggression. According to a higher hierarchy complexity of CSC, different protocols for isolation, expansion, and characterization have been used; however, there are no available resistance biomarkers that allow predicting the clinical response of treatment 5‑fluorouracil (5FU) and oxaliplatin. Therefore, the primary aim of the present study was to analyze the expression of gene resistance on tumors and CSC‑derived isolates from patients CRC. In the present study, adenocarcinomas of the colon and rectum (CRAC) were classified based on an in vitro adenosine triphosphate‑based chemotherapy response assay, as sensitive and resistant and the percentage of CD24 and CD44 markers are evaluated by immunohistochemistry. To isolate resistant colon‑CSC, adenocarcinoma tissues resistant to 5FU and oxaliplatin were evaluated. Finally, all samples were sequenced using a custom assay with chemoresistance‑associated genes to find a candidate gene on resistance colon‑CSC. Results showed that 59% of the CRC tissue analyzed was resistant and had a higher percentage of CD44 and CD24 markers. An association was found in the expression of some genes between the tumor‑resistant tissue and CSC. Overall, isolates of the CSC population CD44+ resistant to 5FU and oxaliplatin demonstrated different expression profiles; however, the present study was able to identify overexpression of the KRT‑18 gene, in most of the isolates. In conclusion, the results of the present study showed overexpression of KRT‑18 in CD44+ cells is associated with chemoresistance to 5FU and oxaliplatin in CRAC.

Targeting the mitochondrial trifunctional protein restrains tumor growth in oxidative lung carcinomas

Metabolic reprogramming is a common hallmark of cancer, but a large variability in tumor bioenergetics exists between patients. Using high-resolution respirometry on fresh biopsies of human lung adenocarcinoma, we identified 2 subgroups reflected in the histologically normal, paired, cancer-adjacent tissue: high (OX+) mitochondrial respiration and low (OX-) mitochondrial respiration. The OX+ tumors poorly incorporated [18F]fluorodeoxy-glucose and showed increased expression of the mitochondrial trifunctional fatty acid oxidation enzyme (MTP; HADHA) compared with the paired adjacent tissue. Genetic inhibition of MTP altered OX+ tumor growth in vivo. Trimetazidine, an approved drug inhibitor of MTP used in cardiology, also reduced tumor growth and induced disruption of the physical interaction between the MTP and respiratory chain complex I, leading to a cellular redox and energy crisis. MTP expression in tumors was assessed using histology scoring methods and varied in negative correlation with [18F]fluorodeoxy-glucose incorporation. These findings provide proof-of-concept data for preclinical, precision, bioenergetic medicine in oxidative lung carcinomas.

Immune checkpoint blockade reprograms systemic immune landscape and tumor microenvironment in obesity-associated breast cancer

Immune checkpoint blockade (ICB) has improved outcomes in some cancers. A major limitation of ICB is that most patients fail to respond, which is partly attributable to immunosuppression. Obesity appears to improve immune checkpoint therapies in some cancers, but impacts on breast cancer (BC) remain unknown. In lean and obese mice, tumor progression and immune reprogramming were quantified in BC tumors treated with anti-programmed death-1 (PD-1) or control. Obesity augments tumor incidence and progression. Anti-PD-1 induces regression in lean mice and potently abrogates progression in obese mice. BC primes systemic immunity to be highly responsive to obesity, leading to greater immunosuppression, which may explain greater anti-PD-1 efficacy. Anti-PD-1 significantly reinvigorates antitumor immunity despite persistent obesity. Laminin subunit beta-2 (Lamb2), downregulated by anti-PD-1, significantly predicts patient survival. Lastly, a microbial signature associated with anti-PD-1 efficacy is identified. Thus, anti-PD-1 is highly efficacious in obese mice by reinvigorating durable antitumor immunity. VIDEO ABSTRACT.

Analysis of TERT Isoforms across TCGA, GTEx and CCLE Datasets

Reactivation of the multi-subunit ribonucleoprotein telomerase is the primary telomere maintenance mechanism in cancer, but it is rate-limited by the enzymatic component, telomerase reverse transcriptase (TERT). While regulatory in nature, TERT alternative splice variant/isoform regulation and functions are not fully elucidated and are further complicated by their highly diverse expression and nature. Our primary objective was to characterize TERT isoform expression across 7887 neoplastic and 2099 normal tissue samples using The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression Project (GTEx), respectively. We confirmed the global overexpression and splicing shift towards full-length TERT in neoplastic tissue. Stratifying by tissue type we found uncharacteristic TERT expression in normal brain tissue subtypes. Stratifying by tumor-specific subtypes, we detailed TERT expression differences potentially regulated by subtype-specific molecular characteristics. Focusing on β-deletion splicing regulation, we found the NOVA1 trans-acting factor to mediate alternative splicing in a cancer-dependent manner. Of relevance to future tissue-specific studies, we clustered cancer cell lines with tumors from related origin based on TERT isoform expression patterns. Taken together, our work has reinforced the need for tissue and tumour-specific TERT investigations, provided avenues to do so, and brought to light the current technical limitations of bioinformatic analyses of TERT isoform expression.

Using proteomic and transcriptomic data to assess activation of intracellular molecular pathways

Analysis of molecular pathway activation is the recent instrument that helps to quantize activities of various intracellular signaling, structural, DNA synthesis and repair, and biochemical processes. This may have a deep impact in fundamental research, bioindustry, and medicine. Unlike gene ontology analyses and numerous qualitative methods that can establish whether a pathway is affected in principle, the quantitative approach has the advantage of exactly measuring the extent of a pathway up/downregulation. This results in emergence of a new generation of molecular biomarkers-pathway activation levels, which reflect concentration changes of all measurable pathway components. The input data can be the high-throughput proteomic or transcriptomic profiles, and the output numbers take both positive and negative values and positively reflect overall pathway activation. Due to their nature, the pathway activation levels are more robust biomarkers compared to the individual gene products/protein levels. Here, we review the current knowledge of the quantitative gene expression interrogation methods and their applications for the molecular pathway quantization. We consider enclosed bioinformatic algorithms and their applications for solving real-world problems. Besides a plethora of applications in basic life sciences, the quantitative pathway analysis can improve molecular design and clinical investigations in pharmaceutical industry, can help finding new active biotechnological components and can significantly contribute to the progressive evolution of personalized medicine. In addition to the theoretical principles and concepts, we also propose publicly available software for the use of large-scale protein/RNA expression data to assess the human pathway activation levels.

Normal tissue adjacent to tumor expression profile analysis developed and validated a prognostic model based on Hippo-related genes in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is the most common malignant disease worldwide. Although the diagnosis and treatment of HCC have greatly improved in the recent years, there is still a lack of accurate methods to predict the prognosis of patients. Evidence has shown that Hippo signaling in tissues adjacent to HCC plays a significant role in HCC development. In the present study, we aimed to construct a model based on the expression of Hippo‐related genes (HRGs) in tissues adjacent to HCC to predict the prognosis of HCC patients.

Methods

Gene expression data of paired normal tissues adjacent to HCC (PNTAH) and clinical information were obtained from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The HRG signature was constructed using four canonical Hippo‐related pathways. Univariate Cox regression analysis was used to screen survival‐related HRGs. LASSO and multivariate Cox regression analyses were used to construct the prognostic model. The true and false positive rates of the model were confirmed using receiver operating characteristic (ROC) analysis.

Results

The prognostic model was constructed based on the expression levels of five HRGs (NF2, MYC, BIRC3, CSNK1E, and MINK1) in PNTAH. The mortality rate of HCC patients increased as the risk score determined by the model increased. Furthermore, the risk score was found to be an independent risk factor for the survival of patients. ROC analysis showed that the prognostic model had a better predictive value than the other conventional clinical parameters. Moreover, the reliability of the prognostic model was confirmed in TCGA‐LIHC cohort. A nomogram was generated to predict patient survival. An exploration of the predictive value of the model in HCC tissues indicated that the model is PNTAH‐specific.

Conclusions

We developed and validated a prognostic model based on the expression levels of five HRGs in PNTAH, and this model should be helpful in predicting the prognosis of patients with HCC.

Migration of BEAS-2B cells enhanced by H1299 cell derived-exosomes

Previous studies reported that exosomes (Exos) secreted by tumor cells could affect the tumor cells themselves and normal cells. However, the effects of exosomes derived from tumor cells on normal cells' migration and mechanical characteristics are rarely reported. This work explores the effects of H1299 cell-derived exosomes (H1299-Exos) on the migration of BEAS-2B cells, and analyzes possible mechanical mechanisms. In the experiments, exosomes were isolated from the culture supernatants of H1299 cells by ultracentrifugation. The H1299-Exos were confirmed by scanning electron microscope (SEM) and western blotting (WB). The BEAS-2B cell migration was assessed using scratch assays. Cytoskeletal structure changes were detected by immunofluorescence. Surface morphology and mechanical properties were measured by atomic force microscopy (AFM). After incubation with H1299-Exos for 48 h, BEAS-2B cells enhanced migration ability, with increased filopodia and cytoskeletal rearrangements. The changes in the morphology and mechanical properties of the cells caused by H1299-Exos were detected using AFM, including the increase in cell length and the decrease in cell height, Young's modulus and adhesion. In short, H1299-Exos promoted the BEAS-2B cell migrations. It indicates that the morphological and mechanical properties can be used as a means to assess normal cell alterations induced by tumor cell derived-exosomes. This provides a method for studying the effects of exosomes secreted by tumor cells on normal cells and the changes in their physical properties.

Field Cancerization in NSCLC: A New Perspective on MicroRNAs in Macrophage Polarization

Lung cancer is currently the first cause of cancer-related death. The major lung cancer subtype is non-small cell lung cancers (NSCLC), which accounts for approximatively 85% of cases. The major carcinogenic associated with lung cancer is tobacco smoke, which produces long-lasting and progressive damage to the respiratory tract. The progressive and diffuse alterations that occur in the respiratory tract of patients with cancer and premalignant lesions have been described as field cancerization. At the level of tumor cells, adjacent tumor microenvironment (TME) and cancerized field are taking place dynamic interactions through direct cell-to-cell communication or through extracellular vesicles. These molecular messages exchanged between tumor and nontumor cells are represented by proteins, noncoding RNAs (ncRNAs) and microRNAs (miRNAs). In this paper, we analyze the miRNA roles in the macrophage polarization at the level of TME and cancerized field in NSCLC. Identifying molecular players that can influence the phenotypic states at the level of malignant cells, tumor microenvironment and cancerized field can provide us new insights into tumor regulatory mechanisms that can be further modulated to restore the immunogenic capacity of the TME. This approach could revert alterations in the cancerized field and could enhance currently available therapy approaches.

Breast Cancer Organoids Model Patient-Specific Response to Drug Treatment

Tumor organoids are tridimensional cell culture systems that are generated in vitro from surgically resected patients' tumors. They can be propagated in culture maintaining several features of the tumor of origin, including cellular and genetic heterogeneity, thus representing a promising tool for precision cancer medicine. Here, we established patient-derived tumor organoids (PDOs) from different breast cancer subtypes (luminal A, luminal B, human epidermal growth factor receptor 2 (HER2)-enriched, and triple negative). The established model systems showed histological and genomic concordance with parental tumors. However, in PDOs, the ratio of diverse cell populations was frequently different from that originally observed in parental tumors. We showed that tumor organoids represent a valuable system to test the efficacy of standard therapeutic treatments and to identify drug resistant populations within tumors. We also report that inhibitors of mechanosignaling and of Yes-associated protein 1 (YAP) activation can restore chemosensitivity in drug resistant tumor organoids.

The CDK6-c-Jun-Sp1-MMP-2 axis as a biomarker and therapeutic target for triple-negative breast cancer

Triple-negative breast cancer (TNBC) has high metastatic, drug-resistance, and recurrence rates, and is characterized by an angiogenic and fibrotic microenvironment that favors cancer malignancy. However, details of the mechanisms underlying malignancy are still largely unknown. Our mouse model indicated that knockdown of CDK6 inhibited lung metastasis significantly compared to parental cells. Immunohistochemical analyses revealed that the levels of collagen and the angiogenic marker matrix metalloproteinase (MMP)-2 were much lower in CDK6-deficient cells. To examine mechanisms in the CDK6-mediated phenotype of cancer cells, we studied its role in MMP-2 expression. CDK6 mediated the recruitment of transcription factors including c-Jun and Sp1 to the MMP2 promoter. Knockdown of CDK6 significantly suppressed the expression of MMP2 mRNA. Consistent with the in vitro data, the expression of CDK6 was positively correlated with the angiogenic and fibrotic tumor microenvironment in TNBC patient tissues as shown by MMP-2 and fibronectin staining, respectively. More importantly, after screening a small molecule library of 31 protein kinase inhibitors, we found that the Raf inhibitor sorafenib displayed the highest cytotoxicity in CDK6-depleted cells. These data indicate that CDK6 serves as an anti-microenvironment target and affects the drug response in retinoblastoma-proficient TNBC, suggesting that combining a CDK6 inhibitor and sorafenib leads to a synthetic effect that may represent a personalized therapeutic approach for patients with TNBC.

Associations between tissue-based CD3+ T-lymphocyte count and colorectal cancer survival in a prospective cohort of older women

Tumor-infiltrating lymphocytes in colorectal cancer (CRC) predict better survival. However, associations between T-lymphocyte count in histologically normal tissues from patients with CRC and survival remain uncertain. We examined associations of CD3+ T-cells in colorectal tumor and histologically normal tissues with CRC-specific and all-cause mortality in the prospective Iowa Women's Health Study. Tissue microarrays were constructed using paraffin-embedded colorectal tissue samples from 464 women with tumor tissues and 314 women with histologically normal tissues (55-69 years at baseline) diagnosed with incident CRC from 1986 to 2002 and followed through 2014 (median follow-up 20.5 years). Three tumor and two histologically normal tissue cores for each patient were immunostained using CD3+ antibody and quantified, and the counts were averaged across the cores in each tissue. Cox proportional hazards regression estimated hazard ratios (HR) and 95% confidence interval (CI) for CRC-specific and all-cause mortality. After adjustment for age at diagnosis, body mass index, smoking status, tumor grade, and stage, HRs (95% CI) for the highest versus lowest tertile of tumor CD3+ score were 0.59 (0.38-0.89) for CRC-specific mortality and 0.82 (0.63-1.05) for all-cause mortality; for histologically normal CD3+ score, the corresponding HRs (95% CI) were 0.47 (0.19-1.17) and 0.50 (0.27-0.90), respectively. The CD3+ score combining the tumor and histologically normal scores was inversely associated with CRC-specific and all-cause mortality. Although the association between tumor CD3+ score and all-cause mortality was not significant, both higher CD3+ T-lymphocyte counts in tumor and histologically normal scores tended to be associated with lower CRC-specific and all-cause mortality.

Role of miRNAs in Sigmoid Colon Cancer: A Search for Potential Biomarkers

The aberrant expression of microRNAs in known to play a crucial role in carcinogenesis. Here, we evaluated the miRNA expression profile of sigmoid colon cancer (SCC) compared to adjacent-to-tumor (ADJ) and sigmoid colon healthy (SCH) tissues obtained from colon biopsy extracted from Brazilian patients. Comparisons were performed between each group separately, considering as significant p-values < 0.05 and |Log2(Fold-Change)| > 2. We found 20 differentially expressed miRNAs (DEmiRNAs) in all comparisons, two of which were shared between SCC vs. ADJ and SCC vs. SCH. We used miRTarBase, and miRTargetLink to identify target-genes of the differentially expressed miRNAs, and DAVID and REACTOME databases for gene enrichment analysis. We also used TCGA and GTEx databases to build miRNA-gene regulatory networks and check for the reproducibility in our results. As findings, in addition to previously known miRNAs associated with colorectal cancer, we identified three potential novel biomarkers. We showed that the three types of colon tissue could be clearly distinguished using a panel composed by the 20 DEmiRNAs. Additionally, we found enriched pathways related to the carcinogenic process in which miRNA could be involved, indicating that adjacent-to-tumor tissues may be already altered and cannot be considered as healthy tissues. Overall, we expect that these findings may help in the search for biomarkers to prevent cancer progression or, at least, allow its early detection, however, more studies are needed to confirm our results.

The Key Genes for Perineural Invasion in Pancreatic Ductal Adenocarcinoma Identified With Monte-Carlo Feature Selection Method

Background

Pancreatic ductal adenocarcinoma (PDAC) is the most aggressive form of pancreatic cancer. Its 5-year survival rate is only 3–5%. Perineural invasion (PNI) is a process of cancer cells invading the surrounding nerves and perineural spaces. It is considered to be associated with the poor prognosis of PDAC. About 90% of pancreatic cancer patients have PNI. The high incidence of PNI in pancreatic cancer limits radical resection and promotes local recurrence, which negatively affects life quality and survival time of the patients with pancreatic cancer.

Objectives

To investigate the mechanism of PNI in pancreatic cancer, we analyzed the gene expression profiles of tumors and adjacent tissues from 50 PDAC patients which included 28 patients with perineural invasion and 22 patients without perineural invasion.

Method

Using Monte-Carlo feature selection and Incremental Feature Selection (IFS) method, we identified 26 key features within which 15 features were from tumor tissues and 11 features were from adjacent tissues.

Results

Our results suggested that not only the tumor tissue, but also the adjacent tissue, was informative for perineural invasion prediction. The SVM classifier based on these 26 key features can predict perineural invasion accurately, with a high accuracy of 0.94 evaluated with leave-one-out cross validation (LOOCV).

Conclusion

The in-depth biological analysis of key feature genes, such as TNFRSF14, XPO1, and ATF3, shed light on the understanding of perineural invasion in pancreatic ductal adenocarcinoma.

Immune Responses and Risk of Triple-negative Breast Cancer: Implications for Higher Rates among African American Women

The etiology of triple-negative breast cancers (TNBC) is poorly understood. As many TNBCs develop prior to the initiation of breast cancer screening or at younger ages when the sensitivity of mammography is comparatively low, understanding the etiology of TNBCs is critical for discovering novel prevention approaches for these tumors. Furthermore, the higher incidence rate of estrogen receptor-negative breast cancers, and specifically, of TNBCs, among young African American women (AAW) versus white women is a source of racial disparities in breast cancer mortality. Whereas immune responses to TNBCs have received considerable attention in relation to prognosis and treatment, the concept that dysregulated immune responses may predispose to the development of TNBCs has received limited attention. We present evidence that dysregulated immune responses are critical in the pathogenesis of TNBCs, based on the molecular biology of the cancers and the mechanisms proposed to mediate TNBC risk factors. Furthermore, proposed risk factors for TNBC, especially childbearing without breastfeeding, high parity, and obesity, are more prevalent among AAW than white women. Limited data suggest genetic differences in immune responses by race, which favor a stronger Thr type 2 (Th2) immune response among AAW than white women. Th2 responses contribute to wound-healing processes, which are implicated in the pathogenesis of TNBCs. Accordingly, we review data on the link between immune responses and TNBC risk and consider whether the prevalence of risk factors that result in dysregulated immunity is higher among AAW than white women.

RNA Sequencing in Comparison to Immunohistochemistry for Measuring Cancer Biomarkers in Breast Cancer and Lung Cancer Specimens

RNA sequencing is considered the gold standard for high-throughput profiling of gene expression at the transcriptional level. Its increasing importance in cancer research and molecular diagnostics is reflected in the growing number of its mentions in scientific literature and clinical trial reports. However, the use of different reagents and protocols for RNA sequencing often produces incompatible results. Recently, we published the Oncobox Atlas of RNA sequencing profiles for normal human tissues obtained from healthy donors killed in road accidents. This is a database of molecular profiles obtained using uniform protocol and reagents settings that can be broadly used in biomedicine for data normalization in pathology, including cancer. Here, we publish new original 39 breast cancer (BC) and 19 lung cancer (LC) RNA sequencing profiles obtained for formalin-fixed paraffin-embedded (FFPE) tissue samples, fully compatible with the Oncobox Atlas. We performed the first correlation study of RNA sequencing and immunohistochemistry-measured expression profiles for the clinically actionable biomarker genes in FFPE cancer tissue samples. We demonstrated high (Spearman's rho 0.65-0.798) and statistically significant (p < 0.00004) correlations between the RNA sequencing (Oncobox protocol) and immunohistochemical measurements for HER2/ERBB2, ER/ESR1 and PGR genes in BC, and for PDL1 gene in LC; AUC: 0.963 for HER2, 0.921 for ESR1, 0.912 for PGR, and 0.922 for PDL1. To our knowledge, this is the first validation that total RNA sequencing of archived FFPE materials provides a reliable estimation of marker protein levels. These results show that in the future, RNA sequencing can complement immunohistochemistry for reliable measurements of the expression biomarkers in FFPE cancer samples.

Prognostic Factors and Tumor Infiltrating Lymphocytes in Triple Negative Breast Cancer

Objective

Triple-negative-breast-cancer (TNBC) is a very heterogenous disease some of which are very aggressive and have poor prognosis. No targeted therapy is available. Immune response and tumor-infiltrating lymphocytes (TIL) can be related to longer disease-free survival (DFS) and overall survival (OS) in TNBC. Family history of cancer can be related poor prognosis, irrespective of genetic mutation.

Materials and Methods

Pathology reports and files of 167 patients operated for TNBC were assessed retrospectively. The effects of lymphocyte infiltration, family history of cancer and other tumor characteristics on prognosis were evaluated. Data of 137 patients was included in statistical analysis.

Results

Univariate-analysis revealed that stage, size of tumor, histological subtype, number of infiltrated axillary lymph-nodes, lymphatic and vascular invasion, choice of adjuvant/neoadjuvant chemotherapy, family history of cancer has a statistically significant effect on DFS. Increase in density of lymphocyte infiltration of tumor has also better a prognostic effect on DFS (p=0.02). In multivariate-analysis, only tumor size and choice of adjuvant/neoadjuvant chemotherapy are found to have statistically significant effect.

Conclusion

Tumor lymphocyte infiltration was found to have a statistically significant better prognostic effect on DFS but not on OS of patients with operated TNBC. This result can be due to variability of therapies administered after recurrence and other confounding factors that may have an effect on OS.

Spatiotemporal dynamics of postoperative functional plasticity in patients with brain tumors in language areas

Postoperative functional neuroimaging provides a unique opportunity to investigate the neural mechanisms that facilitate language network reorganization. Previous studies in patients with low grade gliomas (LGGs) in language areas suggest that postoperative recovery is likely due to functional neuroplasticity in peritumoral and contra-tumoral healthy regions, but have attributed varying degrees of importance to specific regions. In this study, we used Magnetoencephalography (MEG) to investigate functional connectivity changes in peritumoral and contra-tumoral regions after brain tumor resection. MEG recordings of cortical activity during resting-state were obtained from 12 patients with LGGs in left-hemisphere language brain areas. MEG data were recorded before (Pre session), and 3 (Post_1 session) and 6 (Post_2 session) months after awake craniotomy. For each MEG session, we measured the functional connectivity of the peritumoral and contra-tumoral regions to the rest of the brain across the 1-100 Hz frequency band. We found that functional connectivity in the Post_1 and Post_2 sessions was higher than in the Pre session only in peritumoral regions and within the alpha frequency band. Functional connectivity in peritumoral regions did not differ between the Post_1 and Post_2 sessions. Alpha connectivity enhancement in peritumoral regions was observed in all patients regardless of the LGG location. Together, these results suggest that postoperative language functional reorganization occurs in peritumoral regions regardless of the location of the tumor and mostly develops within 3 months after surgery.

EPDR1 up-regulation in human colorectal cancer is related to staging and favours cell proliferation and invasiveness

The finding of novel molecular markers for prediction or prognosis of invasiveness in colorectal cancer (CRC) constitutes an appealing challenge. Here we show the up-regulation of EPDR1 in a prospective cohort of 101 CRC patients, in a cDNA array of 43 patients and in in silico analyses. EPDR1 encodes a protein related to ependymins, a family of glycoproteins involved in intercellular contacts. A thorough statistical model allowed us to conclude that the gene is significantly up-regulated in tumour tissues when compared with normal mucosa. These results agree with those obtained by the analysis of three publicly available databases. EPDR1 up-regulation correlates with the TNM staging parameters, especially T and M. Studies with CRC cell lines revealed that the methylation of a CpG island controls EPDR1 expression. siRNA knocking-down and overexpression of the gene following transient plasmid transfection, showed that EPDR1 favours cell proliferation, migration, invasiveness and adhesion to type I collagen fibres, suggesting a role in epithelial to mesenchymal transition. Both statistical and functional analysis correlated EPDR1 overexpression with invasiveness and dissemination of tumour cells, supporting the inclusion of EPDR1 in panels of genes used to improve molecular subtyping of CRC. Eventually, EPDR1 may be an actionable target.

In situ analysis of Her2 DNA and RNA in retinoblastoma and adjacent retina

Retinoblastoma (RB) is an ocular tumor of early childhood. Current treatments attempt to preserve visual function, but may spare chemoresistant tumor cells. One potential therapeutic target for RB is HER2, (ERBB2), expressed in RB in truncated form. In this study, we tested the hypothesis that Her2 DNA and RNA are expressed in RB tumors and adjacent retina. We examined 24 human RB tumors as well as normal-appearing adjacent retinal tissues for Her2 DNA and RNA expression by in situ hybridization. We also examined 28 RB tumors for HER2 protein immunoreactivity. 21/22 RB tumors expressed Her2 DNA and 14/19 tumors expressed Her2 RNA. In 17 paired cases, there were three cases in which Her2 DNA was detected, but not RNA. We also saw Her2 RNA signal in six instances of "normal" adjacent retinal tissue. Heterogeneous HER2 protein expression in specific tumor regions also was confirmed by quantitative HER2 immunohistochemistry. In summary, Her2 DNA and RNA are expressed in many RB tumors, and in some adjacent ocular tissues, with hetereogenous protein expression throughout. These results may provide important insights regarding RB tumor progression, and drug targeting approaches designed to spare the eye, preserve vision and improve quality of life for RB patients.

Tumor-Infiltrating Lymphocyte Volume Is a Better Predictor of Disease-Free Survival Than Stromal Tumor-Infiltrating Lymphocytes in Invasive Breast Carcinoma

OBJECTIVES

Tumor-infiltrating lymphocytes (TILs) have recently emerged as a prognostic factor in breast cancer. In our previous study, we proposed that tumor stroma should also be considered in the calculation of TILs and we introduced tumor infiltration lymphocyte volume (TILV) in triple-negative breast cancer.

METHODS

We assessed the disease-free survival predictive value of TILV in all subtypes of invasive breast carcinoma and compared the predictive value of TILV with TILs. Differences between disease-free survival curves were determined by using the log-rank test, and Kaplan-Meier survival plots were generated for both groups.

RESULTS

TILV was significantly correlated with disease-free survival in both invasive ductal carcinoma (P = .03) and all subtypes of invasive breast carcinoma (P = .043), whereas TILs failed to show a statistical significance.

CONCLUSIONS

Tumor-stroma ratio needs to be considered in estimation of tumor immunity, and TILV adds more predictive power to TILs.

Vascular density of histologically benign breast tissue from women with breast cancer: associations with tissue composition and tumor characteristics

In breast tumors, it is well established that intratumoral angiogenesis is crucial for malignant progression, but little is known about the vascular characteristics of extratumoral, cancer-adjacent breast. Genome-wide transcriptional data suggest that extratumoral microenvironments may influence breast cancer phenotypes; thus, histologic features of cancer-adjacent tissue may also have clinical implications. To this end, we developed a digital algorithm to quantitate vascular density in approximately 300 histologically benign tissue specimens from breast cancer patients enrolled in the UNC Normal Breast Study (NBS). Specimens were stained for CD31, and vascular content was compared to demographic variables, tissue composition metrics, and tumor molecular features. We observed that the vascular density of cancer-adjacent breast was significantly higher in older and obese women, and was strongly associated with breast adipose tissue content. Consistent with observations that older and heavier women experience higher frequencies of ER+ disease, higher extratumoral vessel density was also significantly associated with positive prognostic tumor features such as lower stage, negative nodal status, and smaller size (<2 cm). These results reveal biological relationships between extratumoral vascular content and body size, breast tissue composition, and tumor characteristics, and suggest biological plausibility for the relationship between weight gain (and corresponding breast tissue changes) and breast cancer progression.

Gastric Normal Adjacent Mucosa Versus Healthy and Cancer Tissues: Distinctive Transcriptomic Profiles and Biological Features

Gastric cancer (GC) is a leading cause of cancer-related deaths in the world. Molecular heterogeneity is a major determinant for the clinical outcomes and an exhaustive tumor classification is currently missing. Histologically normal tissue adjacent to the tumor (NAT) is commonly used as a control in cancer studies, nevertheless a recently published paper described the unique characteristics of the NAT in several tumor types. Little is known about the global gene expression profile of gastric NAT (gNAT) which could be an effective tool for a more realistic definition of GC molecular signature. Here, we integrated data of 512 samples from the Genotype-Tissue Expression project (GETx) and The Cancer Genome Atlas (TCGA) to analyze the transcriptome of healthy gastric tissues, gNAT, and GC samples. We validated TCGA-GETx data mining through inHouse gNAT and GC expression dataset. Differential gene expression together with pathway enrichment analyses, indeed, led to different results when using the gNAT or the healthy tissue as control. Based on our analyses, gNAT showed a peculiar gene signature and biological features, like the estrogen receptor pathways activation, suggesting a molecular behavior partially different from both healthy and GC tissues. Therefore, using gNAT as healthy control tissue in the characterization of tumor associated biological processes and pathways could lead to suboptimal results.

Assessing the Role of the Interleukin-12/STAT4 Axis in Breast Cancer by a Bioinformatics Approach

Interleukin-12 (IL-12) is an anti-tumor cytokine that promotes biological actions through the IL-12/STAT4 axis. Genetic variation and tumor microenvironment dynamics have been identified as critical elements for impaired immune anti-tumor responses. Breast cancer (BC) is a heterogeneous disease classified at the molecular level in several subtypes, each having unique biological and clinical traits. Despite research identifying the relevance of IL-12 in many cancer types, no studies have assessed the role of the IL-12/STAT4 axis in BC. The goal of this study was to evaluate the correlation of the IL-12/STAT4 signaling axis and BC patients' survival in general and in the context of the BC molecular subtypes. Bioinformatics analyses using TCGA data were completed to evaluate the correlation of the IL-12/STAT4 axis and BC. A high expression of important IL-12/STAT4 axis molecules such as the IL-12 receptor genes (IL12RB1 and IL12RB2), STAT4, IFNG and TBX21 were found to significantly increase BC patients' survival rates, especially in the most aggressive BC subtypes such as the luminal B (LumB), HER-2+ and basal like (BL). A possible relevant role of the IL-12/STAT4 axis in BC is suggested by this bioinformatics-study, which might also be subtype-specific. Further studies such as molecular and tumor microenvironment analyses will be required to clarify better the specific role of the IL-12 /STAT4 axis in BC. The results from these additional analyses may potentially improve IL-12-related immunotherapeutic approaches to BC.

RNA sequencing for research and diagnostics in clinical oncology

Molecular diagnostics is becoming one of the major drivers of personalized oncology. With hundreds of different approved anticancer drugs and regimens of their administration, selecting the proper treatment for a patient is at least nontrivial task. This is especially sound for the cases of recurrent and metastatic cancers where the standard lines of therapy failed. Recent trials demonstrated that mutation assays have a strong limitation in personalized selection of therapeutics, consequently, most of the drugs cannot be ranked and only a small percentage of patients can benefit from the screening. Other approaches are, therefore, needed to address a problem of finding proper targeted therapies. The analysis of RNA expression (transcriptomic) profiles presents a reasonable solution because transcriptomics stands a few steps closer to tumor phenotype than the genome analysis. Several recent studies pioneered using transcriptomics for practical oncology and showed truly encouraging clinical results. The possibility of directly measuring of expression levels of molecular drugs' targets and profiling activation of the relevant molecular pathways enables personalized prioritizing for all types of molecular-targeted therapies. RNA sequencing is the most robust tool for the high throughput quantitative transcriptomics. Its use, potentials, and limitations for the clinical oncology will be reviewed here along with the technical aspects such as optimal types of biosamples, RNA sequencing profile normalization, quality controls and several levels of data analysis.

Identification of Novel Susceptibility Loci and Genes for Prostate Cancer Risk: A Transcriptome-Wide Association Study in Over 140,000 European Descendants

Genome-wide association study-identified prostate cancer risk variants explain only a relatively small fraction of its familial relative risk, and the genes responsible for many of these identified associations remain unknown. To discover novel prostate cancer genetic loci and possible causal genes at previously identified risk loci, we performed a transcriptome-wide association study in 79,194 cases and 61,112 controls of European ancestry. Using data from the Genotype-Tissue Expression Project, we established genetic models to predict gene expression across the transcriptome for both prostate models and cross-tissue models and evaluated model performance using two independent datasets. We identified significant associations for 137 genes at P < 2.61 × 10-6, a Bonferroni-corrected threshold, including nine genes that remained significant at P < 2.61 × 10-6 after adjusting for all known prostate cancer risk variants in nearby regions. Of the 128 remaining associated genes, 94 have not yet been reported as potential target genes at known loci. We silenced 14 genes and many showed a consistent effect on viability and colony-forming efficiency in three cell lines. Our study provides substantial new information to advance our understanding of prostate cancer genetics and biology. SIGNIFICANCE: This study identifies novel prostate cancer genetic loci and possible causal genes, advancing our understanding of the molecular mechanisms that drive prostate cancer.

Fatty acids distribution and content in oral squamous cell carcinoma tissue and its adjacent microenvironment

Squamous cell carcinoma of the oral cavity mucosa grows under conditions of poor oxygenation and nutrient scarcity. Reprogramming of lipid biosynthesis accompanies tumor growth, but the conditions under which it occurs are not fully understood. The fatty acid content of the serum, tumor tissue and adjacent tumor microenvironment was measured by gas chromatography in 30 patients with squamous cell carcinoma grade 1-3. Twenty-five fatty acids were identified; their frequencies and percentages in each of the environments were assessed. Nineteen of the twenty-five fatty acids were found in tumor tissue, tumor adjacent tissue and blood serum. Of them, 8 were found in all thirty patients. Percentages of C16:0 and C18:1n9 were highest in the tumor, C18:1n9 and C16:0 were highest in tumor adjacent tissue, and C16:0 and C18:0 were highest in blood serum. The frequencies and amounts of C22:1n13, C22:4n6, C22:5n3 and C24:1 in tumor adjacent tissues were higher than those in blood serum, independent of the tumor grade. The correlations between the amount of fatty acid and tumor grade were the strongest in tumor adjacent tissues. The correlations between particular fatty acids were most prevalent for grade 1+2 tumors and were strongest for grade 3 tumors. In the adjacent tumor microenvironment, lipogenesis was controlled by C22:6w3. In blood serum, C18:1trans11 limited the synthesis of long-chain fatty acids. Our research reveals intensive lipid changes in oral cavity SCC adjacent to the tumor microenvironment and blood serum of the patients. Increase in percentage of some of the FAs in the path: blood serum-tumor adjacent microenvironment-tumor, and it is dependent on tumor grade. This dependency is the most visible in the tumor adjacent environment.

Atlas of RNA sequencing profiles for normal human tissues

Comprehensive analysis of molecular pathology requires a collection of reference samples representing normal tissues from healthy donors. For the available limited collections of normal tissues from postmortal donors, there is a problem of data incompatibility, as different datasets generated using different experimental platforms often cannot be merged in a single panel. Here, we constructed and deposited the gene expression database of normal human tissues based on uniformly screened original sequencing data. In total, 142 solid tissue samples representing 20 organs were taken from post-mortal human healthy donors of different age killed in road accidents no later than 36 hours after death. Blood samples were taken from 17 healthy volunteers. We then compared them with the 758 transcriptomic profiles taken from the other databases. We found that overall 463 biosamples showed tissue-specific rather than platform- or database-specific clustering and could be aggregated in a single database termed Oncobox Atlas of Normal Tissue Expression (ANTE). Our data will be useful to all those working with the analysis of human gene expression.

PAM50 Molecular Intrinsic Subtypes in the Nurses' Health Study Cohorts

BACKGROUND

Modified median and subgroup-specific gene centering are two essential preprocessing methods to assign breast cancer molecular subtypes by PAM50. We evaluated the PAM50 subtypes derived from both methods in a subset of Nurses' Health Study (NHS) and NHSII participants; correlated tumor subtypes by PAM50 with IHC surrogates; and characterized the PAM50 subtype distribution, proliferation scores, and risk of relapse with proliferation and tumor size weighted (ROR-PT) scores in the NHS/NHSII.

METHODS

PAM50 subtypes, proliferation scores, and ROR-PT scores were calculated for 882 invasive breast tumors and 695 histologically normal tumor-adjacent tissues. Cox proportional hazards models evaluated the relationship between PAM50 subtypes or ROR-PT scores/groups with recurrence-free survival (RFS) or distant RFS.

RESULTS

PAM50 subtypes were highly comparable between the two methods. The agreement between tumor subtypes by PAM50 and IHC surrogates improved to fair when Luminal subtypes were grouped together. Using the modified median method, our study consisted of 46% Luminal A, 18% Luminal B, 14% HER2-enriched, 15% Basal-like, and 8% Normal-like subtypes; 53% of tumor-adjacent tissues were Normal-like. Women with the Basal-like subtype had a higher rate of relapse within 5 years. HER2-enriched subtypes had poorer outcomes prior to 1999.

CONCLUSIONS

Either preprocessing method may be utilized to derive PAM50 subtypes for future studies. The majority of NHS/NHSII tumor and tumor-adjacent tissues were classified as Luminal A and Normal-like, respectively.

IMPACT

Preprocessing methods are important for the accurate assignment of PAM50 subtypes. These data provide evidence that either preprocessing method can be used in epidemiologic studies.

Juxtatumoral perinephric fat analysis in clear cell renal cell carcinoma

PURPOSE

The purpose of the study was to evaluate the feasibility of using contrast-enhanced computed tomography (CECT)-based texture analysis (CTTA) metrics to differentiate between juxtatumoral perinephric fat (JPF) surrounding low-grade (ISUP 1-2) versus high-grade (ISUP 3-4) clear cell renal cell carcinoma (ccRCC).

METHODS

In this IRB-approved study, we retrospectively queried the surgical database between June 2009 and April 2016 and identified 83 patients with pathologically confirmed ccRCC (low grade: n = 54, mean age = 61.5 years, 18F/35M; high grade n = 30, mean age = 61.7 years, 8F/22M) who also had pre-operative multiphase CT acquisitions. CT images were transferred to a 3D workstation, and nephrographic phase JPF regions were manually segmented. Using an in-house developed Matlab program, a CTTA panel comprising of texture metrics extracted using six different methods, histogram, 2D- and 3D-Gray-level co-occurrence matrix (GLCM) and Gray-level difference matrix (GLDM), and 2D-Fast Fourier Transform (FFT) analyses, was applied to the segmented images to assess JPF textural heterogeneity in low- versus high-grade ccRCC. Univariate analysis and receiver-operator characteristics (ROC) analysis were used to assess interclass differences in texture metrics and their prediction accuracy, respectively.

RESULTS

All methods except GLCM consistently revealed increased heterogeneity in the JPF surrounding high- versus low-grade ccRCC. FFT showed increased complexity index (p < 0.01). Histogram analysis showed increased kurtosis and positive skewness in (p < 0.03), and GLDM analysis showed decreased measure of correlation coefficient (MCC) (p < 0.04). Several of the GLCM metrics showed statistically significant (p < 0.04) textural differences between the two groups, but with no consistent trend. ROC analysis showed that MCC in GLCM analysis had an area under the curve of 0.75.

CONCLUSIONS

Our study suggests that CTTA of ccRCC shows statistically significant textural differences in JPF surrounding high- versus low-grade ccRCC.

Molecular mechanisms linking high body mass index to breast cancer etiology in post-menopausal breast tumor and tumor-adjacent tissues

PURPOSE

In post-menopausal women, high body mass index (BMI) is an established breast cancer risk factor and is associated with worse breast cancer prognosis. We assessed the associations between BMI and gene expression of both breast tumor and adjacent tissue in estrogen receptor-positive (ER+) and estrogen receptor-negative (ER-) diseases to help elucidate the mechanisms linking obesity with breast cancer biology in 519 post-menopausal women from the Nurses' Health Study (NHS) and NHSII.

METHODS

Differential gene expression was analyzed separately in ER+ and ER- disease both comparing overweight (BMI ≥ 25 to < 30) or obese (BMI ≥ 30) women to women with normal BMI (BMI < 25), and per 5 kg/m² increase in BMI. Analyses controlled for age and year of diagnosis, physical activity, alcohol consumption, and hormone therapy use. Gene set enrichment analyses were performed and validated among a subset of post-menopausal cases in The Cancer Genome Atlas (for tumor) and Polish Breast Cancer Study (for tumor-adjacent).

RESULTS

No gene was differentially expressed by BMI (FDR < 0.05). BMI was significantly associated with increased cellular proliferation pathways, particularly in ER+ tumors, and increased inflammation pathways in ER- tumor and ER- tumor-adjacent tissues (FDR < 0.05). High BMI was associated with upregulation of genes involved in epithelial-mesenchymal transition in ER+ tumor-adjacent tissues.

CONCLUSIONS

This study provides insights into molecular mechanisms of BMI influencing post-menopausal breast cancer biology. Tumor and tumor-adjacent tissues provide independent information about potential mechanisms.

Stroma modifies relationships between risk factor exposure and age-related epithelial involution in benign breast

Delayed age-related lobular involution has been previously associated with elevated breast cancer risk. However, intraindividual variability in epithelial involution status within a woman is undefined. We developed a novel measure of age-related epithelial involution, density of epithelial nuclei in epithelial areas using digital image analysis in combination with stromal characteristics (percentage of section area comprising stroma). Approximately 1800 hematoxylin and eosin stained sections of benign breast tissue were evaluated from 416 participants having breast surgery for cancer or benign conditions. Two to sixteen slides per woman from different regions of the breast were studied. Epithelial involution status varied within a woman and as a function of stromal area. Percentage stromal area varied between samples from the same woman (median difference between highest and lowest stromal area within a woman was 7.5%, but ranged from 0.01 to 86.7%). Restricting to women with at least 10% stromal area (N = 317), epithelial nuclear density decreased with age (-637.1 cells/mm² per decade of life after age 40, p < 0.0001), increased with mammographic density (457.8 cells/mm² per increasing BI-RADs density category p = 0.002), and increased non-significantly with recent parity, later age at first pregnancy, and longer and more recent oral contraceptive use. These associations were attenuated in women with mostly fat samples (<10% stroma (N = 99)). Thirty-one percent of women evaluated had both adequate stroma (≥10%) and mostly fat (<10% stroma) regions of breast tissue, with the probability of having both types increasing with the number breast tissue samplings. Several breast cancer risk factors are associated with elevated age-related epithelial content, but associations depend upon stromal context. Stromal characteristics appear to modify relationships between risk factor exposures and breast epithelial involution.

A transcriptome-wide association study of 229,000 women identifies new candidate susceptibility genes for breast cancer

The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P < 5.82 × 10-6, including 14 genes at loci not yet reported for breast cancer. We silenced 13 genes and showed an effect for 11 on cell proliferation and/or colony-forming efficiency. Our study provides new insights into breast cancer genetics and biology.

Intra-individual Gene Expression Variability of Histologically Normal Breast Tissue

Several studies have sought to identify novel transcriptional biomarkers in normal breast or breast microenvironment to predict tumor risk and prognosis. However, systematic efforts to evaluate intra-individual variability of gene expression within normal breast have not been reported. This study analyzed the microarray gene expression data of 288 samples from 170 women in the Normal Breast Study (NBS), wherein multiple histologically normal breast samples were collected from different block regions and different sections at a given region. Intra-individual differences in global gene expression and selected gene expression signatures were quantified and evaluated in association with other patient-level factors. We found that intra-individual reliability was relatively high in global gene expression, but differed by signatures, with composition-related signatures (i.e., stroma) having higher intra-individual variability and tumorigenesis-related signatures (i.e., proliferation) having lower intra-individual variability. Histological stroma composition was the only factor significantly associated with heterogeneous breast tissue (defined as > median intra-individual variation; high nuclear density, odds ratio [OR] = 3.42, 95% confidence interval [CI] = 1.15–10.15; low area, OR = 0.29, 95% CI = 0.10–0.86). Other factors suggestively influencing the variability included age, BMI, and adipose nuclear density. Our results underscore the importance of considering intra-individual variability in tissue-based biomarker development, and have important implications for normal breast research.

Engineering Breast Cancer Microenvironments and 3D Bioprinting

The extracellular matrix (ECM) is a critical cue to direct tumorigenesis and metastasis. Although two-dimensional (2D) culture models have been widely employed to understand breast cancer microenvironments over the past several decades, the 2D models still exhibit limited success. Overwhelming evidence supports that three dimensional (3D), physiologically relevant culture models are required to better understand cancer progression and develop more effective treatment. Such platforms should include cancer-specific architectures, relevant physicochemical signals, stromal-cancer cell interactions, immune components, vascular components, and cell-ECM interactions found in patient tumors. This review briefly summarizes how cancer microenvironments (stromal component, cell-ECM interactions, and molecular modulators) are defined and what emerging technologies (perfusable scaffold, tumor stiffness, supporting cells within tumors and complex patterning) can be utilized to better mimic native-like breast cancer microenvironments. Furthermore, this review emphasizes biophysical properties that differ between primary tumor ECM and tissue sites of metastatic lesions with a focus on matrix modulation of cancer stem cells, providing a rationale for investigation of underexplored ECM proteins that could alter patient prognosis. To engineer breast cancer microenvironments, we categorized technologies into two groups: (1) biochemical factors modulating breast cancer cell-ECM interactions and (2) 3D bioprinting methods and its applications to model breast cancer microenvironments. Biochemical factors include matrix-associated proteins, soluble factors, ECMs, and synthetic biomaterials. For the application of 3D bioprinting, we discuss the transition of 2D patterning to 3D scaffolding with various bioprinting technologies to implement biophysical cues to model breast cancer microenvironments.

Correlated metabolomic, genomic, and histologic phenotypes in histologically normal breast tissue

Breast carcinogenesis is a multistep process accompanied by widespread molecular and genomic alterations, both in tumor and in surrounding microenvironment. It is known that tumors have altered metabolism, but the metabolic changes in normal or cancer-adjacent, nonmalignant normal tissues and how these changes relate to alterations in gene expression and histological composition are not well understood. Normal or cancer-adjacent normal breast tissues from 99 women of the Normal Breast Study (NBS) were evaluated. Data of metabolomics, gene expression and histological composition was collected by mass spectrometry, whole genome microarray, and digital image, respectively. Unsupervised clustering analysis determined metabolomics-derived subtypes. Their association with genomic and histological features, as well as other breast cancer risk factors, genomic and histological features were evaluated using logistic regression. Unsupervised clustering of metabolites resulted in two main clusters. The metabolite differences between the two clusters suggested enrichment of pathways involved in lipid metabolism, cell growth and proliferation, and migration. Compared with Cluster 1, subjects in Cluster 2 were more likely to be obese (body mass index ≥30 kg/m2, p<0.05), have increased adipose proportion (p<0.01) and associated with a previously defined Active genomic subtype (p<0.01). By the integrated analyses of histological, metabolomics and transcriptional data, we characterized two distinct subtypes of non-malignant breast tissue. Further research is needed to validate our findings, and understand the potential role of these alternations in breast cancer initiation, progression and recurrence.

Construction of differential mRNA-lncRNA crosstalk networks based on ceRNA hypothesis uncover key roles of lncRNAs implicated in esophageal squamous cell carcinoma

Increasing evidence has indicated that lncRNAs acting as competing endogenous RNAs (ceRNAs) play crucial roles in tumorigenesis, metastasis and diagnosis of cancer. However, the function of lncRNAs as ceRNAs involved in esophageal squamous cell carcinoma (ESCC) is still largely unknown. In this study, clinical implications of two intrinsic subtypes of ESCC were identified based on expression profiles of lncRNA and mRNA. ESCC subtype-specific differential co-expression networks between mRNAs and lncRNAs were constructed to reveal dynamic changes of their crosstalks mediated by miRNAs during tumorigenesis. Several well-known cancer-associated lncRNAs as the hubs of the two networks were firstly proposed in ESCC. Based on the ceRNA mechanism, we illustrated that the"loss" of miR-186-mediated PVT1-mRNA and miR-26b-mediated LINC00240-mRNA crosstalks were related to the two ESCC subtypes respectively. In addition, crosstalks between LINC00152 and EGFR, LINC00240 and LOX gene family were identified, which were associated with the function of "response to wounding" and "extracellular matrix-receptor interaction". Furthermore, functional cooperation of multiple lncRNAs was discovered in the two differential mRNA-lncRNA crosstalk networks. These together systematically uncovered the roles of lncRNAs as ceRNAs implicated in ESCC.