Novel biomarkers of metastatic cancer

Role of fibrilins in human cancer: A narrative review

Background

Fibrillin is one of the extracellular matrix glycoproteins and participates in forming microfibrils found in many connective tissues. The microfibrils enable the elasticity and stretching properties of the ligaments and support connective tissues. There are three isoforms of fibrillin molecules identified in mammals: fibrillin 1 (FBN1), fibrillin 2 (FBN2), and fibrillin 3.

Objective

Multiple studies have shown that mutations in these genes or changes in their expression levels can be related to various diseases, including cancers. In this study, we focus on reviewing the role of the fibrillin family in multiple cancers.

Methods and Results

We performed a comprehensive literature review to search PubMed and Google Scholar for studies published so far on fibrillin gene expression and its role in cancers. In this review, we have focused on the expression of FBN1 and FBN2 genes in cancers such as the lung, intestine, ovary, pancreatic ductal, esophagus, and thyroid.

Conclusion

Altogether various studies showed higher expression of fibrillins in different tumor tissues correlated with the patient's survival. However, there are controversial findings, as some other cancers showed hypermethylated FBN promoters with lower gene expression levels.

Visualization of Metastatic Lung Cancer with TiNIR

The development of efficient biomarkers and probes for monitoring and treating cancer, specifically metastatic cancer, is a critical research area that can have a significant impact on both patient outcomes and drug discovery. In this context, TiNIR has been developed to detect tumor-initiating cells (TICs), with heme oxygenase 2 (HO2) as a promising therapeutic biomarker for tumor-initiating cells. In this study, TiNIR has demonstrated its effectiveness as an in vivo metastatic lung cancer tracker, highlighting its potential as a valuable tool in cancer research and therapy. The development of innovative approaches that selectively target metastatic cancers represents a promising avenue for improving survival rates and enhancing the quality of life of cancer patients.

Identification of Prognostic Biomarkers for Suppressing Tumorigenesis and Metastasis of Hepatocellular Carcinoma through Transcriptome Analysis

Cancer is one of the deadliest diseases developed through tumorigenesis and could be fatal if it reaches the metastatic phase. The novelty of the present investigation is to explore the prognostic biomarkers in hepatocellular carcinoma (HCC) that could develop glioblastoma multiforme (GBM) due to metastasis. The analysis was conducted using RNA-seq datasets for both HCC (PRJNA494560 and PRJNA347513) and GBM (PRJNA494560 and PRJNA414787) from Gene Expression Omnibus (GEO). This study identified 13 hub genes found to be overexpressed in both GBM and HCC. A promoter methylation study showed these genes to be hypomethylated. Validation through genetic alteration and missense mutations resulted in chromosomal instability, leading to improper chromosome segregation, causing aneuploidy. A 13-gene predictive model was obtained and validated using a KM plot. These hub genes could be prognostic biomarkers and potential therapeutic targets, inhibition of which could suppress tumorigenesis and metastasis.

The role of cytokeratin 7/20 coordination revisited-Machine learning identifies improved interpretative algorithms for cell block immunohistochemistry in aspirates of metastatic carcinoma

BACKGROUND

Fine-needle aspiration (FNA) is a robust diagnostic technique often used for tissue diagnosis of metastatic carcinoma. For interpretation of FNA cytology, cell block immunohistochemistry (IHC) and clinicocytologic parameters are indispensable. In this review of a large cohort, the current report: 1) describes clinicocytologic parameters and immunoprofiles of aspirates of metastatic carcinoma, 2) compares the predictivity of immunostains and classical approaches for IHC interpretation, and 3) describes machine learning-based algorithms for IHC interpretation.

METHODS

Aspirates of metastatic carcinoma that had IHC performed were retrieved. Clinicocytologic parameters, IHC results, the corresponding primary site, and histologic diagnoses were recorded. By using machine learning, decision trees for predicting the primary site were generated, their performance was compared with 2 human-designed algorithms, and the primary site was suggested in the historical diagnosis.

RESULTS

In total, 1145 cases were identified. The 6 most populated groups were selected for machine learning and predictive analysis. With IHC input, the decision tree achieved a concordance rate of 94.5% and overall accuracy of 83.6%, which improved to 95.3% and 85.8%, respectively, when clinical data were incorporated and exceeded the human-designed IHC algorithms (P < .001). The historical diagnosis was more accurate unless indeterminate diagnoses were regarded as discordant (P < .001). CDX2 and TTF-1 immunostains had the highest weight in model accuracy, occupied the root of the decision trees, scored higher as features of importance, and outperformed the predictive power of cytokeratins 7 and 20.

CONCLUSIONS

Cytokeratins 7 and 20 may be superseded in immunostaining panels, including organ-specific immunostains such as CDX2 and TTF-1. Machine learning generates algorithms that surpasses human-designed algorithms but is inferior to expert assessment integrating clinical and cytologic assessment.

A Six-microRNA Signature Nomogram for Preoperative Prediction of Tumor Deposits in Colorectal Cancer

Purpose

Tumor deposits (TDs) are acknowledged negative prognostic factors in colorectal cancer (CRC), and their pathogenesis remains a puzzle. This study aimed to construct and validate a nomogram available for preoperative TDs prediction in CRC patients.

Patients and Methods

Patients from the Surveillance, Epidemiology, and End Results (SEER) and the cancer genome atlas (TCGA) databases were randomly divided into training and validation sets according to the sample size ratio of 7:3. Univariate logistic regression was performed for identifying differentially expressed microRNAs between TDs and non-TDs. Nomograms for TDs prediction were developed from the multivariate logistic regression model with least absolute shrinkage and selection operator and were validated internally in terms of accuracy, calibration, and clinical utility. Based on the target genes, pathways tightly associated with TDs were selected using enrichment analysis.

Results

Six clinicopathologic factors and expressions of six microRNAs (miR-614, miR-1197, miR-4770, miR-3136, miR-3173, and miR-4636) differed significantly between TDs and non-TDs CRC patients from the SEER and TCGA training sets. We compared potential prediction discrimination between two nomograms: a clinicopathologic nomogram and a six-microRNA signature nomogram. The six-microRNA signature nomogram revealed better accuracy than the clinicopathologic one for TDs prediction (AUC values of 0.96 and 0.93 in the validation cohort). The calibration plots and decision curve analysis demonstrated that the six-microRNA signature nomogram had better validity and a greater prognostic benefit versus the clinicopathologic one for TDs prediction. Calcium signaling pathways were closely associated with roles of the six microRNAs in TDs of CRC patients.

Conclusion

The six-microRNA signature nomogram can be used as an efficient tool for preoperative TDs prediction in CRC patients.

Cancer of Unknown Primary Site: Real Entity or Misdiagnosed Disease?

Metastasis is a late event in the progression of any tumour. However, invasive cancers are occasionally detected in the form of metastatic lesions without a clearly detectable primary tumour. Cancer of unknown primary site (CUP) is defined as a confirmed metastatic tumour, with unknown primary tumour site, despite the standardized diagnostic approach that includes clinical history, routine laboratory tests, and complete physical examination. Due to the lack of basic research on its primary causes, CUP is appropriately termed an 'orphan' cancer. Nevertheless, CUP accounts for 2-5% of diagnosed malignancies. To date, it is unclear whether CUP is an entity with primary dormancy as its hallmark or an entity with genetic abnormalities that cause it to manifest as a primary metastatic disease. In this review, we discuss different aspects of CUP, including its current diagnostic methods, angiogenesis effectors, relationship with cancer stem cells and current treatments.

Development of a preoperative prediction nomogram for lymph node metastasis in colorectal cancer based on a novel serum miRNA signature and CT scans

BACKGROUND

Preoperative prediction of lymph node (LN) status is of crucial importance for appropriate treatment planning in patients with colorectal cancer (CRC). In this study, we sought to develop and validate a non-invasive nomogram model to preoperatively predict LN metastasis in CRC.

METHODS

Development of the nomogram entailed three subsequent stages with specific patient sets. In the discovery set (n = 20), LN-status-related miRNAs were screened from high-throughput sequencing data of human CRC serum samples. In the training set (n = 218), a miRNA panel-clinicopathologic nomogram was developed by logistic regression analysis for preoperative prediction of LN metastasis. In the validation set (n = 198), we validated the above nomogram with respect to its discrimination, calibration and clinical application.

FINDINGS

Four differently expressed miRNAs (miR-122-5p, miR-146b-5p, miR-186-5p and miR-193a-5p) were identified in the serum samples from CRC patients with and without LN metastasis, which also had regulatory effects on CRC cell migration. The combined miRNA panel could provide higher LN prediction capability compared with computed tomography (CT) scans (P < .0001 in both the training and validation sets). Furthermore, a nomogram integrating the miRNA-based panel and CT-reported LN status was constructed in the training set, which performed well in both the training and validation sets (AUC: 0.913 and 0.883, respectively). Decision curve analysis demonstrated the clinical usefulness of the nomogram.

INTERPRETATION

Our nomogram is a reliable prediction model that can be conveniently and efficiently used to improve the accuracy of preoperative prediction of LN metastasis in patients with CRC.

FOXC2 and CLIP4 : a potential biomarker for synchronous metastasis of ≤7-cm clear cell renal cell carcinomas

Renal cell carcinomas (RCC) smaller than 7-cm are heterogeneous and exhibit metastatic potential in approximately 15% of cases. Although large-scale characterization of mutations in clear cell RCC (ccRCC), the most common RCC subtype, has been established, the genetic alterations related to ≤7-cm ccRCCs undergoing synchronous metastasis are poorly understood. To discover biomarkers that can be used to estimate the risk of synchronous metastasis in these ccRCC patients, we performed whole exome sequencing on the formalin-fixed paraffin-embedded (FFPE) samples of 10 ccRCC patients with ≤7-cm tumors and synchronous metastasis and expanded our study using The Cancer Genome Atlas (TCGA) ccRCC dataset (n = 201). Recurrent mutations were selected according to functional prediction and statistical significance. Mutations in three candidate genes, RELN (1 out of 10), FOXC2 (1 out of 10), and CLIP4 (2 out of 10) were found in expanded analysis using a TCGA cohort. Furthermore, siRNA-mediated target gene knockdown (FOXC2 and CLIP4) and overexpression (RELN) assays showed that FOXC2 and CLIP4 significantly increased cell migration and viability in ccRCCs. Our study demonstrated that FOXC2 and CLIP4 activity correlates to the presence of ≤7-cm ccRCCs with synchronous metastasis and may be potential molecular predictors of synchronous metastasis of ≤7-cm ccRCCs.

Co-amplification at lower denaturation-temperature PCR combined with unlabled-probe high-resolution melting to detect KRAS codon 12 and 13 mutations in plasma-circulating DNA of pancreatic adenocarcinoma cases

BACKGROUND

The aim of our study was to establish COLD-PCR combined with an unlabeled-probe HRM approach for detecting KRAS codon 12 and 13 mutations in plasma-circulating DNA of pancreatic adenocarcinoma (PA) cases as a novel and effective diagnostic technique.

MATERIALS AND METHODS

We tested the sensitivity and specificity of this approach with dilutions of known mutated cell lines. We screened 36 plasma-circulating DNA samples, 24 from the disease control group and 25 of a healthy group, to be subsequently sequenced to confirm mutations. Simultaneously, we tested the specimens using conventional PCR followed by HRM and then used target-DNA cloning and sequencing for verification. The ROC and respective AUC were calculated for KRAS mutations and/or serum CA 19-9.

RESULTS

It was found that the sensitivity of Sanger reached 0.5% with COLD- PCR, whereas that obtained after conventional PCR did 20%; that of COLD-PCR based on unlabeled-probe HRM, 0.1%. KRAS mutations were identified in 26 of 36 PA cases (72.2%), while none were detected in the disease control and/or healthy group. KRAS mutations were identified both in 26 PA tissues and plasma samples. The AUC of COLD-PCR based unlabeled probe HRM turned out to be 0.861, which when combined with CA 19-9 increased to 0.934.

CONCLUSIONS

It was concluded that COLD-PCR with unlabeled-probe HRM can be a sensitive and accurate screening technique to detect KRAS codon 12 and 13 mutations in plasma-circulating DNA for diagnosing and treating PA.

miR-10b promotes migration and invasion in nasopharyngeal carcinoma cells

MicroRNA-10b (miR-10b) has been reported to play an important role in some types of cancer, but the effects and possible mechanisms of action of miR-10b in the metastasis of nasopharyngeal carcinoma cells (NPC) have not been explored. The aim of the present study was to investigate the function of miR-10b in nasopharyngeal carcinoma and to determine the molecular mechanisms underlying its action. The MTT assay was used to assess proliferation of CNE-2Z cells. Wound healing and transwell migration assays were applied to assess cell migration and invasion, while and expression of E-cadherin and MMP-9 were detected using Western blot analysis. Real-time PCR was employed to detect the expression of genes related to migration and invasion and the 2-??Ct method was used to calculate the degree of expression. MTT assay showed the expression of miR-10b to have no effect on the proliferation of NPC cell lines. The wound healing assay showed that miR-10b mimics promoted the mobility and invasion of NPC cell lines. Inhibitors of miR-10b reduced the ability of NPC cell lines to migrate and invade. In addition, the expression of genes related to migration and invasion, such as E-cadherin, vimentin, and MMP-9, were confirmed to be different in the CNE-2Z NPC cell line transfected with miR-10b mimics and with miR-10b inhibitors. In the present study, miR-10b was found to upregulate the expression of MMP-9 and knockdown of miR-10b was found to significantly downregulate the expression of E-cadherin. On the whole, these results showed that miR-10b plays an important role in the invasion and metastasis of NPC cells.

High-level expression of CXCR4 in breast cancer is associated with early distant and bone metastases

Metastasis is the most life-threatening complication in all cancers. The chemokine receptor 4 (CXCR4) is expressed at high levels in many breast-cancer tumors and may modulate metastasis. We compared the time-to-metastasis and the sites of metastasis between breast-cancer tumors expressing CXCR4 at high or low levels. We enrolled 191 early breast cancer patients in our study. The expression of CXCR4 was evaluated using immunohistochemical staining, and the patients were divided into low-level (CXCR4-) and high-level (CXCR4+) CXCR4 expression groups. Associations between the patients' level of CXCR4 expression and their basic clinical characteristics, time-to-metastasis, and metastatic sites were examined using a Cox proportional-hazards regression model. A total of 107 CXCR4+ patients (56 %) were identified. No statistical differences were evident in basic characteristics between the CXCR4+ and CXCR4- groups. The CXCR4+ group had a higher incidence of distant metastasis during the first year (10.3 % versus 1.1 %, P = 0.009) and shorter event-free survival (17.43 months versus 27.5 months, P = 0.026) than those of the CXCR4- group. The CXCR4+ group also had a higher incidence of bone metastasis (P = 0.008) than the CXCR4- group. No significant difference in metastasis sites in other organs was observed between the two groups. A high level of CXCR4 expression in breast cancer is associated with early distant and bone metastases. The CXCR4+ phenotype may be a useful predictor for the prevention of early treatment failure and bone metastasis in breast cancer patients. This retrospective study shows that a high expression of CXCR4 in breast cancer is associated with earlier distant metastasis and bone metastasis in breast cancer.

Use of PD biomarkers to drive dose selection and early clinical decision making

A major challenge facing the development of new therapies is the high level of compound attrition in late-stage clinical studies. A key factor in reducing these unsustainable levels of attrition is the successful evaluation of the level of drug effect on its target pathway in early development, otherwise known as testing the compound mechanism. Incorporation of PD biomarkers into Phase I/II trials to demonstrate compound binding to its molecular target and the subsequent modulation of downstream pathways enables early testing of compound mechanism and provides a data-driven framework for decisions on compound progression. This review will discuss the identification and validation of such 'fit-for-purpose' PD biomarkers, and case studies illustrating their use and value in dose selection and accelerating the clinical development of small-molecule drugs will be described.