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Key Points Precision medicine seeks to identify and classify individual patients so that optimal treatment decisions can be made. Nations are recognizing this area of research by developing national cohorts from which to collect data and developing regulatory guidelines on biomarkers. The cost of genetic sequencing and other 'omics' technologies has decreased while the quality of data they generate has increased. Thus, immense amounts of molecular data are being derived from cohort studies to begin developing new biomarkers to classify patients into subtypes. The development of biomarkers is largely limited by the following factors: low statistical power in rare subtypes; risk of false-positive findings in studies that do not validate their findings in a separate cohort and/or conduct concomitant mechanistic experiments; and technical reproducibility concerns. Genomics and protein immunohistochemistry have led the way for developing biomarkers. Other molecular measurements (for example, metabolomics and microbiomics) are still in preliminary stages and are often not validated in another cohort. Integrating different types of molecules into a biomarker panel, along with other patient data, is the future of precision medicine; however, the sheer number of potential combinations of data types complicates the concerns about statistical power and reproducibility. Currently, improved biomarkers are needed to differentiate lung nodules identified by new US national screening recommendations into non-cancer, cancer with poor survival probability and cancer with higher survival probability subtypes, to provide thousands of individuals with precise treatment decisions. This Review summarizes the successes and challenges of using different types of molecules as biomarkers, using lung cancer as a key illustrative example. This article also discusses the future of precision medicine and national-level efforts to better treat patients with cancer. Precision medicine relies on validated biomarkers with which to better classify patients by their probable disease risk, prognosis and/or response to treatment. Although affordable 'omics'-based technology has enabled faster identification of putative biomarkers, the validation of biomarkers is still stymied by low statistical power and poor reproducibility of results. This Review summarizes the successes and challenges of using different types of molecule as biomarkers, using lung cancer as a key illustrative example. Efforts at the national level of several countries to tie molecular measurement of samples to patient data via electronic medical records are the future of precision medicine research.

TP53 mutants (mutp53) are involved in the pathogenesis of most human cancers. Specific mutp53 proteins gain oncogenic functions (GOFs) distinct from the tumor suppressor activity of the wild-type protein. Tumor-associated macrophages (TAMs), a hallmark of solid tumors, are typically correlated with poor prognosis. Here, we report a non-cell-autonomous mechanism, whereby human mutp53 cancer cells reprogram macrophages to a tumor supportive and anti-inflammatory state. The colon cancer cells harboring GOF mutp53 selectively shed miR-1246-enriched exosomes. Uptake of these exosomes by neighboring macrophages triggers their miR-1246-dependent reprogramming into a cancer-promoting state. Mutp53-reprogammed TAMs favor anti-inflammatory immunosuppression with increased activity of TGF-β. These findings, associated with poor survival in colon cancer patients, strongly support a microenvironmental GOF role for mutp53 in actively engaging the immune system to promote cancer progression and metastasis. p53 gain of function mutants (mutp53) are involved in the pathogenesis of most human cancers. Here, the authors show that mutp53 regulates the tumor microenvironment by inducing the release of specific exosomes containing miR-1246 that once received by macrophages turns them into tumor supportive macrophages.

Key Points Single nucleotide polymorphisms (SNPs) in microRNA (miRNA) genes (miR-SNPs) can be predicted to affect function by modulating the transcription of the primary transcript, pri-miRNA and pre-miRNA processing and maturation, or miRNA–mRNA interactions. Functional support for each of these mechanisms has been found for several individual miR-SNPs. SNPs in mature miRNAs and miRNA binding sites function analogously to modulate the miRNA–mRNA interaction and create or destroy miRNA binding sites. Several elements have to converge for an miRNA binding site SNP to be considered functional: the SNP must have a proven association with cancer, both the miRNA and its predicted target must be expressed in the tissue, and the allelic changes must result in differential binding of the miRNA and affect expression of the target gene. Computational prediction of miRNA binding sites and up-to-date coverage of SNPs is an essential part of these studies. Programs such as Patrocles and PolymiRTS intercalate and cross-reference these data with dbSNP information, and as such are invaluable in aiding the search for polymorphic miRNA binding sites. Case–control studies have provided evidence for an association of miR-SNPs and SNPs in miRNA-binding sites and cancer risk. These studies differ in the degree of functional support for the predicted interaction and mechanistic insight, as well as validation status. Although still lacking biological validation, SNPs in the miRNA processing machinery are likely to affect the miRNAome as a whole, perhaps leading to overall suppression of miRNA output. Despite several reported associations, none of the studies of SNPs in miRNA processing machinery has been independently validated, nor has the biological mechanisms of how they affect miRNA maturation and cancer been delineated. IsomiRs are miRNA structural variants that may arise from variable cleavage sites for DROSHA and DICER1 in the hairpin. A few isomiRs have been implicated in cancer, but associations with cancer risk have not been established. Both the regulatory and coding regions of genes can harbour miRNA binding sites, but research in this area remains scant. Sensitive alleles identified in epidemiological studies, but with obscure functional roles, should perhaps be tested under miRNA prediction algorithms that are not limited to the 3′ untranslated region of genes, particularly if evidence indicates that altered expression of that gene can be associated with the phenotypes. The presence of single nucleotide polymorphisms in microRNA genes, their processing machinery and target binding sites might affect cancer risk, treatment efficacy and patient prognosis. This evolving field of cancer biology is discussed in this Review. Many studies have highlighted the role that microRNAs have in physiological processes and how their deregulation can lead to cancer. More recently, it has been proposed that the presence of single nucleotide polymorphisms in microRNA genes, their processing machinery and target binding sites affects cancer risk, treatment efficacy and patient prognosis. In reviewing this new field of cancer biology, we describe the methodological approaches of these studies and make recommendations for which strategies will be most informative in the future.

Colorectal cancer (CRC) remains one of the major cancer types and cancer related death worldwide. Sensitive, non-invasive biomarkers that can facilitate disease detection, staging and prediction of therapeutic outcome are highly desirable to improve survival rate and help to determine optimized treatment for CRC. The small non-coding RNAs, microRNAs (miRNAs), have recently been identified as critical regulators for various diseases including cancer and may represent a novel class of cancer biomarkers. The purpose of this study was to identify and validate circulating microRNAs in human plasma for use as such biomarkers in colon cancer. By using quantitative reverse transcription-polymerase chain reaction, we found that circulating miR-141 was significantly associated with stage IV colon cancer in a cohort of 102 plasma samples. Receiver operating characteristic (ROC) analysis was used to evaluate the sensitivity and specificity of candidate plasma microRNA markers. We observed that combination of miR-141 and carcinoembryonic antigen (CEA), a widely used marker for CRC, further improved the accuracy of detection. These findings were validated in an independent cohort of 156 plasma samples collected at Tianjin, China. Furthermore, our analysis showed that high levels of plasma miR-141 predicted poor survival in both cohorts and that miR-141 was an independent prognostic factor for advanced colon cancer. We propose that plasma miR-141 may represent a novel biomarker that complements CEA in detecting colon cancer with distant metastasis and that high levels of miR-141 in plasma were associated with poor prognosis.

Bile salt hydrolase (BSH) in Bacteroides is considered a potential drug target for obesity-related metabolic diseases, but its involvement in colon tumorigenesis has not been explored. BSH-expressing Bacteroides is found at high abundance in the stools of colorectal cancer (CRC) patients  with overweight and in the feces of a high-fat diet (HFD)-induced CRC mouse model. Colonization of B. fragilis 638R, a strain with low BSH activity, overexpressing a recombinant bsh gene from B. fragilis NCTC9343 strain, results in increased unconjugated bile acids in the colon and accelerated progression of CRC under HFD treatment. In the presence of high BSH activity, the resultant elevation of unconjugated deoxycholic acid and lithocholic acid activates the G-protein-coupled bile acid receptor, resulting in increased β-catenin-regulated chemokine (C-C motif) ligand 28 (CCL28) expression in colon tumors. Activation of the β-catenin/CCL28 axis leads to elevated intra-tumoral immunosuppressive CD25 + FOXP3 + T reg cells. Blockade of the β-catenin/CCL28 axis releases the immunosuppression to enhance the intra-tumoral anti-tumor response, which decreases CRC progression under HFD treatment. Pharmacological inhibition of BSH reduces HFD-accelerated CRC progression, coincident with suppression of the β-catenin/CCL28 pathway. These findings provide insights into the pro-carcinogenetic role of Bacteroides in obesity-related CRC progression and characterize BSH as a potential target for CRC prevention and treatment. Non-enterotoxigenic Bacteroides fragilis (NTBF) is abundant in colorectal cancer (CRC) patients and in a high-fat diet (HFD)-induced CRC model. Here the authors show that bile salt hydrolase-expressing NTBF is enriched in CRC patients with overweight and promotes tumor growth in an HFD-induced CRC mouse model.

Background Lung cancer is the leading cancer diagnosis worldwide and the number one cause of cancer deaths. Exposure to cigarette smoke, the primary risk factor in lung cancer, reduces epithelial barrier integrity and increases susceptibility to infections. Herein, we hypothesize that somatic mutations together with cigarette smoke generate a dysbiotic microbiota that is associated with lung carcinogenesis. Using lung tissue from 33 controls and 143 cancer cases, we conduct 16S ribosomal RNA (rRNA) bacterial gene sequencing, with RNA-sequencing data from lung cancer cases in The Cancer Genome Atlas serving as the validation cohort. Results Overall, we demonstrate a lower alpha diversity in normal lung as compared to non-tumor adjacent or tumor tissue. In squamous cell carcinoma specifically, a separate group of taxa are identified, in which Acidovorax is enriched in smokers. Acidovorax temporans is identified within tumor sections by fluorescent in situ hybridization and confirmed by two separate 16S rRNA strategies. Further, these taxa, including Acidovorax , exhibit higher abundance among the subset of squamous cell carcinoma cases with TP53 mutations, an association not seen in adenocarcinomas. Conclusions The results of this comprehensive study show both microbiome-gene and microbiome-exposure interactions in squamous cell carcinoma lung cancer tissue. Specifically, tumors harboring TP53 mutations, which can impair epithelial function, have a unique bacterial consortium that is higher in relative abundance in smoking-associated tumors of this type. Given the significant need for clinical diagnostic tools in lung cancer, this study may provide novel biomarkers for early detection.

Colon cancer (CC) and rectal cancer (RC) are synonymously called colorectal cancer (CRC). Based on our experience in basic and clinical research as well as routine work in the field, the term CRC should be abandoned. We analyzed the available data from the literature and results from our multicenter Research Group Oncology of Gastrointestinal Tumors termed FOGT to confirm or reject this hypothesis. Anatomically, the risk of developing RC is four times higher than CC, while physical activity helps to prevent CC but not RC. Obvious differences exist in molecular carcinogenesis, pathology, surgical topography and procedures, and multimodal treatment. Therefore, we conclude that CC is not the same as RC. The term “CRC” should no longer be used as a single entity in basic and clinical research as well as other areas of classification.

Small, noncoding RNAs are short untranslated RNA molecules, some of which have been associated with cancer development. Recently we showed that a class of small RNAs generated during the maturation process of tRNAs (tRNA-derived small RNAs, hereafter “tsRNAs”) is dysregulated in cancer. Specifically, we uncovered tsRNA signatures in chronic lymphocytic leukemia and lung cancer and demonstrated that the ts-4521/3676 cluster (now called “ts-101” and “ts-53,” respectively), ts-46, and ts-47 are down-regulated in these malignancies. Furthermore, we showed that tsRNAs are similar to Piwi-interacting RNAs (piRNAs) and demonstrated that ts-101 and ts-53 can associate with PiwiL2, a protein involved in the silencing of transposons. In this study, we extended our investigation on tsRNA signatures to samples collected from patients with colon, breast, or ovarian cancer and cell lines harboring specific oncogenic mutations and representing different stages of cancer progression. We detected tsRNA signatures in all patient samples and determined that tsRNA expression is altered upon oncogene activation and during cancer staging. In addition, we generated a knockedout cell model for ts-101 and ts-46 in HEK-293 cells and found significant differences in gene-expression patterns, with activation of genes involved in cell survival and down-regulation of genes involved in apoptosis and chromatin structure. Finally, we overexpressed ts-46 and ts-47 in two lung cancer cell lines and performed a clonogenic assay to examine their role in cell proliferation. We observed a strong inhibition of colony formation in cells overexpressing these tsRNAs compared with untreated cells, confirming that tsRNAs affect cell growth and survival.

Background Squamous cell carcinoma (SqCC) is a subtype of non-small cell lung cancer for which patient prognosis remains poor. The extracellular matrix (ECM) is critical in regulating cell behavior; however, its importance in tumor aggressiveness remains to be comprehensively characterized. Methods Multi-omics data of SqCC human tumor specimens was combined to characterize ECM features associated with initiation and recurrence. Penalized logistic regression was used to define a matrix risk signature for SqCC tumors and its performance across a panel of tumor types and in SqCC premalignant lesions was evaluated. Consensus clustering was used to define prognostic matreotypes for SqCC tumors. Matreotype-specific tumor biology was defined by integration of bulk RNAseq with scRNAseq data, cell type deconvolution, analysis of ligand-receptor interactions and enriched biological pathways, and through cross comparison of matreotype expression profiles with aging and idiopathic pulmonary fibrosis lung profiles. Results This analysis revealed subtype-specific ECM signatures associated with tumor initiation that were predictive of premalignant progression. We identified an ECM-enriched tumor subtype associated with the poorest prognosis. In silico analysis indicates that matrix remodeling programs differentially activate intracellular signaling in tumor and stromal cells to reinforce matrix remodeling associated with resistance and progression. The matrix subtype with the poorest prognosis resembles ECM remodeling in idiopathic pulmonary fibrosis and may represent a field of cancerization associated with elevated cancer risk. Conclusions Collectively, this analysis defines matrix-driven features of poor prognosis to inform precision medicine prevention and treatment strategies towards improving SqCC patient outcome.