Triple Negative Breast Cancer (TNBC) is aggressive, metastatic and drug-resistant, limiting the spectrum of effective therapeutic options for breast cancer patients. To date, anti-angiogenic agents have had limited success in the treatment of systemic breast cancer, possibly due to the exacerbation of tumor hypoxia and increased metastasis. Hypoxia drives increased expression of downstream effectors, including Carbonic Anhydrase IX (CAIX), a critical functional component of the pro-survival machinery required by hypoxic tumor cells. Here, we used the highly metastatic, CAIX-positive MDA-MB-231 LM2-4 orthotopic model of TNBC to investigate whether combinatorial targeting of CAIX and angiogenesis impacts tumor growth and metastasis in vivo to improve efficacy. The administration of a small molecule inhibitor of CAIX, SLC-0111, significantly reduced overall metastatic burden, whereas exposure to sunitinib increased hypoxia and CAIX expression in primary tumors, and failed to inhibit metastasis. The administration of SLC-0111 significantly decreased primary tumor vascular density and permeability, and reduced metastasis to the lung and liver. Furthermore, combining sunitinib and SLC-0111 significantly reduced both primary tumor growth and sunitinib-induced metastasis to the lung. Our findings suggest that targeting angiogenesis and hypoxia effectors in combination holds promise as a novel rational strategy for the effective treatment of patients with TNBC.

Anti-PD-L1 antibody monotherapy shows limited efficacy in a significant proportion of the patients. A common explanation for the inefficacy is a lack of anti-tumor effector cells in the tumor microenvironment (TME). Recombinant human interleukin-15 (hIL15), a potent immune stimulant, has been investigated in clinical trial with encouraging results. However, hIL15 is constrained by the short half-life of hIL15 and a relatively unfavorable pharmacokinetics profile. We developed a recombinant fusion IL15 protein composed of human IL15 (hIL15) and albumin binding domain (hIL15-ABD) and explored the therapeutic efficacy and immune regulation of hIL-15, hIL15-ABD and/or combination with anti-PD-L1 on CT26 murine colon cancer (CC) and B16-F10 murine melanoma models. We demonstrated that hIL15-ABD has significant inhibitory effect on the CT26 and B16-F10 tumor growths as compared to hIL-15. hIL-15-ABD not only showed superior half-life and pharmacokinetics data than hIL-15, but also enhance anti-tumor efficacy of antibody against PD-L1 via suppressive effect on accumulation of Tregs and MDSCs and activation of NK and CD8+T cells. Immune suppressive factors including VEGF and IDO were also decreased by combination treatment. hIL15-ABD combined with anti-PD-L1 antibody increased the activity of anti-tumor effector cells involved in both innate and adaptive immunities, decreased the TME's immunosuppressive cells, and showed greater anti-tumor effect than that of either monotherapy.

Accumulating evidence points to a link between circadian clock dysfunction and the molecular events that drive tumorigenesis. Here, we investigated the connection between the circadian clock and the hallmarks of cancer in an in vitro model of colorectal cancer (CRC). We used a cross-platform data normalization method to concatenate and compare available microarray and RNA-sequencing time series data of CRC cell lines derived from the same patient at different disease stages. Our data analysis suggests differential regulation of molecular pathways between the CRC cells and identifies several of the circadian and likely clock-controlled genes (CCGs) as cancer hallmarks and circadian drug targets. Notably, we found links of the CCGs to Huntington's disease (HD) in the metastasis-derived cells. We then investigated the impact of perturbations of our candidate genes in a cohort of 439 patients with colon adenocarcinoma retrieved from the Cancer Genome Atlas (TCGA). The analysis revealed a correlation of the differential expression levels of the candidate genes with the survival of patients. Thus, our study provides a bioinformatics workflow that allows for a comprehensive analysis of circadian properties at different stages of colorectal cancer, and identifies a new association between cancer and HD.

Fatal metastasis occurs when circulating tumor cells (CTCs) disperse through the blood to initiate a new tumor at specific sites distant from the primary tumor. CTCs have been classically defined as nucleated cells positive for epithelial cell adhesion molecule and select cytokeratins (EpCAM/CK/DAPI), while negative for the common lymphocyte marker CD45. The enumeration of CTCs allows an estimation of the overall metastatic burden in breast cancer patients, but challenges regarding CTC heterogeneity and metastatic propensities persist, and their decryption could improve therapies. CTCs from metastatic breast cancer (mBC) patients were captured using the RareCyteTM Cytefinder II platform. The Lin- and Lin+ (CD45+) cell populations isolated from the blood of three of these mBC patients were analyzed by single-cell transcriptomic methods, which identified a variety of immune cell populations and a cluster of cells with a distinct gene expression signature, which includes both cells expressing EpCAM/CK ("classic" CTCs) and cells possessing an array of genes not previously associated with CTCs. This study put forward notions that the identification of these genes and their interactions will promote novel areas of analysis by dissecting properties underlying CTC survival, proliferation, and interaction with circulatory immune cells. It improves upon capabilities to measure and interfere with CTCs for impactful therapeutic interventions.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and lethal cancers, with a 5-year survival rate of less than 5%. In fact, complete surgical resection remains the only curative treatment. However, fewer than 20% of patients are candidates for surgery at the time of presentation. Hence, there is a critical need to identify diagnostic biomarkers with potential clinical utility in this pathology. In this context, metabolomics could be a powerful tool to search for new robust biomarkers. Comparative metabolomic profiling was performed in serum samples from 59 unresectable PDAC patients and 60 healthy controls. Samples were analyzed by using an untargeted metabolomics workflow based on liquid chromatography, coupled to high-resolution mass spectrometry in positive and negative electrospray ionization modes. Univariate and multivariate analysis allowed the identification of potential candidates that were significantly altered in PDAC patients. A panel of nine candidates yielded excellent diagnostic capacities. Pathway analysis revealed four altered pathways in our patients. This study shows the potential of liquid chromatography coupled to high-resolution mass spectrometry as a diagnostic tool for PDAC. Furthermore, it identified novel robust biomarkers with excellent diagnostic capacities.

Breast cancer (BC) is the malignant neoplasm with the highest mortality rate in women and female dogs are good models to study BC.

Cisplatin (cis-diamminedichloroplatinum II [CDDP] ) is a well-known chemotherapeutic drug that has been used for the treatment of various types of human cancers, including head and neck cancer. Cisplatin exerts anticancer effects by causing DNA damage, replication defects, transcriptional inhibition, cell cycle arrest, and the induction of apoptosis. However, drug resistance is one of the most serious problems with cancer chemotherapy, and it causes expected therapeutic effects to not always be achieved. Here, we analyzed global microRNA (miRNA) expression in CD44 standard form (CD44s)-expressing SAS cells, and we identified miR-629-3p as being responsible for acquiring anticancer drug resistance in head and neck cancer. The introduction of miR-629-3p expression inhibited apoptotic cell death under cisplatin treatment conditions, and it promoted cell migration. Among the computationally predicted target genes of miR-629-3p, we found that a number of gene expressions were suppressed by the transfection with miR-629-3p. Using a xenografting model, we showed that miR-629-3p conferred cisplatin resistance to SAS cells. Clinically, increased miR-629-3p expression tended to be associated with decreased survival in head and neck cancer patients. In conclusion, our data suggest that the increased expression of miR-629-3p provides a mechanism of cisplatin resistance in head and neck cancer and may serve as a therapeutic target to reverse chemotherapy resistance.

The combined analysis of circulating cell-free (tumor) DNA (cfDNA/ctDNA) and circulating cell-free (tumor) RNA (cfRNA/ctRNA) shows great promise in determining the molecular profile of cancer patients. Optimization of the workflow is necessary to achieve consistent and reproducible results. In this study, we compared five centrifugation protocols for the optimal yield of both cfDNA/ctDNA and cfRNA/ctRNA. These protocols varied in centrifugation speed, ambient temperature, time, and number of centrifugation steps. Samples from 33 participants were collected in either BD Vacutainer K₂EDTA (EDTA) tubes or cell-free DNA BCT® (Streck) tubes. cfDNA concentration and fragment size, and cfRNA concentration were quantitated in all samples by digital droplet PCR (ddPCR) and quantitative PCR (qPCR). The KRAS-mutated ctDNA and ctRNA fraction was determined via ddPCR. In EDTA tubes, the protocol generating both plasma and platelets was found to produce high quality cfDNA and cfRNA concentrations. Two-step, high-speed centrifugation protocols were associated with high cfDNA but low cfRNA concentrations. High cfRNA concentrations were generated by a one-step, low-speed protocol. However, this coincided with a high amount of genomic DNA (gDNA) contamination. In Streck tubes, two-step, high-speed centrifugation protocols also generated good quality, high cfDNA concentration. However, these tubes are not compatible with cfRNA analysis.

Our previous integrative study in gastric cancer discovered cryptic promoter activation events that drive the expression of important developmental genes. However, it was unclear if such cancer-associated epigenetic changes occurred in cancer cells or other cell types in bulk tissue samples. An integrative analysis consisting of RNA-Seq and H3K4me3 ChIP-Seq was used. This workflow was applied to a set of matched normal lung tissues and non-small cell lung cancer (NSCLC) tissues, for which the stroma and tumor cell parts could be isolated by laser-microdissection microscopy (LMD). RNA-Seq analysis showed subtype-specific differential expressed genes and enriched pathways in NSCLC. ChIP-Seq analysis results suggested that the proximal altered H3K4me3 regions were located at differentially expressed genes involved in cancer-related pathways, while altered distal H3K4me3 regions were annotated with enhancer activity of cancer regulatory genes. Interestingly, integration with ENCODE data revealed that proximal tumor-gained promoters were associated with EZH2 and SUZ12 occupancies, which are the core components of polycomb repressive complex 2 (PRC2). This study used LMD on clinical samples for an integrative analysis to overcome the tissue heterogeneity problem in cancer research. The results also contribute to the overall understanding of genetic and epigenetic dysregulation of lung malignancy.

Agnostic biomarkers such as gene fusions allow to address cancer patients to targeted therapies; however, the low prevalence of these alterations across common malignancies poses challenges and needs a feasible and sensitive diagnostic process. RNA-based targeted next generation sequencing was performed on 125 samples of patients affected either by colorectal carcinoma, melanoma, or lung adenocarcinoma lacking genetic alterations in canonical driver genes, or by a colorectal carcinoma with microsatellite instability. Gene fusion rates were compared with in silico data from MSKCC datasets. For NTRK gene fusion detection we also employed a multitarget qRT-PCR and pan-TRK immunohistochemistry. Gene fusions were detected in 7/55 microsatellite instable colorectal carcinomas (12.73%), and in 4/70 of the "gene driver free" population (5.71%: 3/28 melanomas, 10.7%, and 1/12 lung adenocarcinomas, 8.3%). Fusion rates were significantly higher compared with the microsatellite stable and "gene driver positive" MSKCC cohorts. Pan-TRK immunohistochemistry showed 100% sensitivity, 91.7% specificity, and the occurrence of heterogeneous and/or subtle staining patterns. The enrichment of gene fusions in this "real-world" cohort highlights the feasibility of a workflow applicable in clinical practice. The heterogeneous expression in NTRK fusion positive tumours unveils challenging patterns to recognize and raises questions on the effective translation of the chimeric protein.

Preoperative prediction of microvascular invasion (MVI) is of importance in hepatocellular carcinoma (HCC) patient treatment management. Plenty of radiomics models for MVI prediction have been proposed. This study aimed to elucidate the role of radiomics models in the prediction of MVI and to evaluate their methodological quality. The methodological quality was assessed by the Radiomics Quality Score (RQS), and the risk of bias was evaluated by the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2). Twenty-two studies using CT, MRI, or PET/CT for MVI prediction were included. All were retrospective studies, and only two had an external validation cohort. The AUC values of the prediction models ranged from 0.69 to 0.94 in the test cohort. Substantial methodological heterogeneity existed, and the methodological quality was low, with an average RQS score of 10 (28% of the total). Most studies demonstrated a low or unclear risk of bias in the domains of QUADAS-2. In conclusion, a radiomics model could be an accurate and effective tool for MVI prediction in HCC patients, although the methodological quality has so far been insufficient. Future prospective studies with an external validation cohort in accordance with a standardized radiomics workflow are expected to supply a reliable model that translates into clinical utilization.

In Ovarian Cancer (OC), the analysis of single circulating tumor cells (sCTCs) might help to investigate genetic tumor evolution during the course of treatment. Since common CTC identification features failed to reliably detect CTCs in OC, we here present a workflow for their detection and genomic analysis. Blood of 13 high-grade serous primary OC patients was analyzed, using negative immunomagnetic enrichment, followed by immunofluorescence staining and imaging for Hoechst, ERCC1, CD45, CD11b and cytokeratin (CK) and sCTC sorting with the DEPArrayTM NxT. The whole genome of single cells was amplified and profiled for copy number variation (CNV). We detected: Type A-cells, epithelial (Hoechstpos, ERCC1pos, CD45neg, CD11bpos, CKpos); Type B-cells, potentially epithelial (Hoechstpos, ERCC1pos, CD45neg, CD11bpos, CKneg) and Type C-cells, potentially mesenchymal (Hoechstpos, ERCC1pos, CD45neg, CD11bneg, CKneg). In total, we identified five (38.5%) patients harboring sCTCs with an altered CN profile, which were mainly Type A-cells (80%). In addition to inter-and intra-patient genomic heterogeneity, high numbers of Type B- and C-cells were identified in every patient with their aberrant character only confirmed in 6.25% and 4.76% of cases. Further identification markers and studies in the course of treatment are under way to expand sCTC analysis for the identification of tumor evolution in OC.

Circulating atypical cells (CAC) are released from a primary tumour site into peripheral blood and are indicators of cancer metastasis. CAC occur at very low frequency in circulating blood, and their detection remains challenging. Moreover, white blood cells (WBC) are the major contaminant in enriched CAC samples. Here, we developed matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) as a novel CAC characterization platform. Main spectra profiles (MSP) of normal and cancer cells were generated by MALDI-TOF MS, and a cell-main spectra database was then compiled and analysed using the MALDI Biotyper software. Logarithmic scores accurately predicted distinct cell types. The feasibility of this workflow was then validated using simulated samples, which were prepared by 5000 WBC of three healthy individuals spiked with varying numbers (3, 6, 12, 25, 50, and 100) of lung, colon, or prostate cancer cells. MALDI-TOF MS was able to detect cancer cells down to six cells over the background noise of 5000 WBC with significantly higher predictive scores as compared to WBC alone. Further development of cell-MSP database to cover all cancer types sourced from cell lines and patient tumours may enable the use of MALDI-TOF MS as a cancer-screening platform in clinical settings in the future.

Muscle invasive bladder cancer (MIBC) is a malignancy with considerable heterogeneity. The MIBC tumor microenvironment (TME) is highly complex, comprising diverse phenotypes and spatial architectures. The complexity of the MIBC TME must be characterized to provide potential targets for precision therapy. Herein, an integrated combination of mass cytometry and imaging mass cytometry was used to analyze tumor cells, immune cells, and TME spatial characteristics of 44 MIBC patients. We detected tumor and immune cell clusters with abnormal phenotypes. In particular, we identified a previously overlooked cancer stem-like cell cluster (ALDH+PD-L1+ER-β-) that was strongly associated with poor prognosis. We elucidated the different spatial architectures of immune cells (excluded, infiltrated, and deserted) and tumor-associated collagens (curved, stretched, directionally distributed, and chaotic) in the MIBC TME. The present study is the first to provide in-depth insight into the complexity of the MIBC TME at the single-cell level. Our results will improve the general understanding of the heterogeneous characteristics of MIBC, potentially facilitating patient stratification and personalized therapy.

Renal cell carcinoma (RCC) is known for its variable clinical behavior and outcome, including heterogeneity in developing relapse or metastasis. Recent data highlighted the potential of somatic mutations as promising biomarkers for risk stratification in RCC. Likewise, the analysis of circulating tumor DNA (ctDNA) for such informative somatic mutations (liquid biopsy) is considered an important advance for precision oncology in RCC, allowing to monitor molecular disease evolution in real time. However, our knowledge about the utility of ctDNA analysis in RCC is limited, in part due to the lack of RCC-appropriate assays for ctDNA analysis. Here, by interrogating different blood compartments in xenograft models, we identified plasma cell-free (cf) DNA and extracellular vesicles (ev) DNA enriched for RCC-associated ctDNA. Additionally, we developed sensitive targeted sequencing and bioinformatics workflows capable of detecting somatic mutations in RCC-relevant genes with allele frequencies ≥ 0.5%. Applying this assay to patient-matched tumor and liquid biopsies, we captured tumor mutations in cf- and ev-DNA fractions isolated from the blood, highlighting the potentials of both fractions for ctDNA analysis. Overall, our study presents an RCC-appropriate sequencing assay and workflow for ctDNA analysis and provides a proof of principle as to the feasibility of detecting tumor-specific mutations in liquid biopsy in RCC patients.

Immunotherapy has transformed the management of patients with advanced melanoma, with five-year overall survival rates reaching 52% for combination immunotherapies blocking the cytotoxic T-lymphocyte-associated antigen-4 (CTLA4) and programmed cell death-1 (PD1) immune axes. Yet, our understanding of local and systemic determinants of immunotherapy response and resistance is restrained by the paucity of preclinical models, particularly those for anti-PD1 monotherapy. We have therefore generated a novel murine model of melanoma by integrating key immunotherapy response biomarkers into the model development workflow. The resulting YUMM3.3UVRc34 (BrafV600E; Cdkn2a-/-) model demonstrated high mutation burden and response to interferon (IFN)γ, including induced expression of antigen-presenting molecule MHC-I and the principal PD1 ligand PD-L1, consistent with phenotypes of human melanoma biopsies from patients subsequently responding to anti-PD1 monotherapy. Syngeneic immunosufficient mice bearing YUMM3.3UVRc34 tumors demonstrated durable responses to anti-PD1, anti-CTLA4, or combined treatment. Immunotherapy responses were associated with early on-treatment changes in the tumor microenvironment and circulating T-cell subsets, and systemic immunological memory underlying protection from tumor recurrence. Local and systemic immunological landscapes associated with immunotherapy response in the YUMM3.3UVRc34 melanoma model recapitulate immunotherapy responses observed in melanoma patients and identify discrete immunological mechanisms underlying the durability of responses to anti-PD1 and anti-CTLA4 treatments.

(1) Background: Extracellular vesicles (EVs) have emerged as crucial players in the communication between cells in both physiological and pathological scenarios. The functions of EVs are strongly determined by their molecular content, which includes all bioactive molecules, such as proteins, lipids, RNA, and, as more recently described, double-stranded DNA. It has been shown that in oncological settings DNA associated with EVs (EV-DNA) is representative of the genome of parental cells and that it reflects the mutational status of the tumor, gaining much attention as a promising source of biomarker mutant DNA. However, one of the challenges in studies of EV-DNA is the lack of standardization of protocols for the DNA extraction from EVs, as well as ways to assess quality control, which hinders its future implementation in clinics. (2) Methods: We performed a comprehensive comparison of commonly used approaches for EV-DNA extraction by assessing DNA quantity, quality, and suitability for downstream analyses. (3) Results: We here established strategic points to consider for EV-DNA preparation for mutational analyses, including qPCR and NGS. (4) Conclusions: We put in place a workflow that can be applied for the detection of clinically relevant mutations in the EV-DNA of cancer patients.

Histomorphologic types of gastric cancer (GC) have significant prognostic values that should be considered during treatment planning. Because the thorough quantitative review of a tissue slide is a laborious task for pathologists, deep learning (DL) can be a useful tool to support pathologic workflow. In the present study, a fully automated approach was applied to distinguish differentiated/undifferentiated and non-mucinous/mucinous tumor types in GC tissue whole-slide images from The Cancer Genome Atlas (TCGA) stomach adenocarcinoma dataset (TCGA-STAD). By classifying small patches of tissue images into differentiated/undifferentiated and non-mucinous/mucinous tumor tissues, the relative proportion of GC tissue subtypes can be easily quantified. Furthermore, the distribution of different tissue subtypes can be clearly visualized. The patch-level areas under the curves for the receiver operating characteristic curves for the differentiated/undifferentiated and non-mucinous/mucinous classifiers were 0.932 and 0.979, respectively. We also validated the classifiers on our own GC datasets and confirmed that the generalizability of the classifiers is excellent. The results indicate that the DL-based tissue classifier could be a useful tool for the quantitative analysis of cancer tissue slides. By combining DL-based classifiers for various molecular and morphologic variations in tissue slides, the heterogeneity of tumor tissues can be unveiled more efficiently.

Clinical diagnosis of hepatocellular carcinoma (HCC) relies heavily on radiological imaging. However, information pertaining to liver cancer treatment such as the proliferation status is lacking. Imaging tumor proliferation can be valuable in patient management. This study investigated 18F-labeled clofarabine ([18F]CFA) targeting deoxycytidine kinase (dCK) for PET imaging of dCK-dependent proliferation in HCC. Since clinical PET scans showed a high liver background uptake of [18F]CFA, the aim of this study was to reduce this liver background uptake. A clinically relevant animal model of spontaneously developed HCC in the woodchucks was used for imaging experiments. Several modifiers were tested and compared with the baseline PET scan: Forodesine, probenecid, and cold clofarabine, all applied before the hot [18F]CFA injection to evaluate the reduction in liver background uptake. Application of forodesine before hot [18F]CFA injection did not reduce the background uptake. Instead, it increased the background by 11.6-36.3%. Application of probenecid also increased the liver background uptake by 16.6-32.1%. Cold CFA application did reduce the liver background uptake of [18F]CFA, comparing to the baseline scan. Combining cold CFA with [18F]CFA for PET imaging of liver cancers is a promising strategy, worthy of further clinical evaluation.

While intratumour genetic heterogeneity of primary clear cell renal cell carcinoma (ccRCC) is well characterized, the genomic profiles of metastatic ccRCCs are seldom studied. We profiled the genomes and transcriptomes of a primary tumour and matched metastases to better understand the evolutionary processes that lead to metastasis. In one ccRCC patient, four regions of the primary tumour, one region of the thrombus in the inferior vena cava, and four lung metastases (including one taken after pegylated (PEG)-interferon therapy) were analysed separately. Each sample was analysed for copy number alterations and somatic mutations by whole exome sequencing. We also evaluated gene expression profiles for this patient and 15 primary tumour and 15 metastasis samples from four additional patients. Copy number profiles of the index patient showed two distinct subgroups: one consisted of three primary tumours with relatively minor copy number changes, the other of a primary tumour, the thrombus, and the lung metastases, all with a similar copy number pattern and tetraploid-like characteristics. Somatic mutation profiles indicated parallel clonal evolution with similar numbers of private mutations in each primary tumour and metastatic sample. Expression profiling of the five patients revealed significantly changed expression levels of 57 genes between primary tumours and metastases, with enrichment in the extracellular matrix cluster. The copy number profiles suggest a punctuated evolution from a subregion of the primary tumour. This process, which differentiated the metastases from the primary tumours, most likely occurred rapidly, possibly even before metastasis formation. The evolutionary patterns we deduced from the genomic alterations were also reflected in the gene expression profiles.