Introduction

This study aimed to build up prognosis model and discover novel prognostic biomarkers for colon adenocarcinoma (COAD) based on ferroptosis-related lncRNA analysis.

Aims & Methods

The RNA-sequencing data and clinical information were obtained from TCGA database. Ferroptosis-related genes used were downloaded from the GSEA database. We screened ferroptosis-related lncRNAs with correlation coefficient >0.3 and P <0.001. Firstly, the prognostic value of ferroptosis-related lncRNAs with P < 0.05 was assessed by univariate Cox regression. Then, the results were submitted to Least Absolute Shrinkage and Selection Operator (LASSO) regression. Eventually, the results of LASSO were incorporated into a multivariate Cox model in order to calculate risk scores. We developed a risk score formula for predicting overall survival (OS), based on a linear combination of ferroptosis-related lncRNAs expression levels multiplied with a regression coefficient. According to the median risk score, patients were divided into high-risk and low-risk groups. K-M method and log-rank test were applied to draw the survival curve of highly and lowly expressed prognostic ferroptosis-related lncRNAs. Cox regression was utilized to build up an independent prognostic model. The index of concordance (C-index), calibration curves, and receiver operating characteristic (ROC) curves were applied to assess the accuracy of the model. The clinical data were included in multivariate Cox regression in order to confirm whether the risk score was an independent indicator for the prognosis.

Results

An eight-lncRNAs signature was built up, 7 lncRNAs (ZEB1-AS1, AL354993.2, LINC02381, AP001505.1, NCK1-DT, CD27-AS1, AC068580.3) predicted a poor prognosis, and SNHG16 predicted a good prognosis. The formula of the risk score calculation: risk score = (0.557*ZEB1-AS1) + (0.199*AL354993.2) + (0.183*LINC02381) + (0.079*AP001505.1) + (0.279*NCK1-DT) + (0.107*CD27-AS1) + (0.532* AC068580.3 － (0.138* SNHG16). The low-risk group had longer OS than the high-risk group (P<0.001, log-rank test), so the risk score might be related to the OS of COAD patients. According to the forest map, the hazard ratios of risk score in univariate and multivariate Cox regression analyses were 1.354 (95% CI: 1.228-1.494, P <0.001) and 1.343 (95%CI = 1.202 -1.500, P <0.001), respectively. Either in univariate or multivariate analysis, the risk score was of independent significance for prognosis. The AUC of ROC curve in 3-years survival was 0.737 and 0.785 in 5-years survival. According to the multivariate factor ROC curves, besides risk score, age and TNM stage also had a good ability to predict overall survival, while gender had a weak ability. Next, risk score, age T, M, N and stage were included into the nomogram. As indicated in the nomogram, risk score and stage were the largest contributors to OS of COAD patients. The risk score increased with stage, demonstrating that this ferroptosis-related lncRNA signature could predict the clinical progression of COAD. We divided the clinical sample data into three groups to obtain the calibration diagram, showing that the OS predicted by the model was in a good agreement with the observed clinically. The C-index of the prognostic model was 0.795 (se=0.028).

Conclusion

A signature based on eight ferroptosis-related lncRNAs is efficient in predicting the prognosis of patients with COAD. The eight lncRNAs may be novel prognostic and therapeutic biomarkers for COAD. The specific mechanism of how ferroptosis-related lncRNAs affects tumor biological behavior remains to be researched.

Introduction

Colorectal cancer (CRC) is one of the most common malignancies worldwide, and early detection significantly improves patient outcomes. Long non-coding RNAs (lncRNAs) are >200 nucleotide transcripts that regulate gene expression and are frequently dysregulated in cancer. Notably, certain lncRNAs are overexpressed during colorectal tumorigenesis and detectable in circulation, making them promising non-invasive biomarkers. This study aimed to identify circulating lncRNAs with progressive expression changes along the adenoma-carcinoma sequence and evaluate their potential as early diagnostic markers for CRC.

Aims & Methods

We performed bioinformatic screening of three public gene expression datasets (GSE117606, GSE289499, GSE154548) containing colorectal normal, adenoma, and carcinoma tissues. Twelve lncRNA candidates showing linear differential expression across the adenoma-to-carcinoma sequence were identified. The five most significantly dysregulated lncRNAs (ZFAS1, FOXP4-AS1, CRNDE, UCA1, SNHG17) were selected for further validation. Plasma samples were collected from healthy controls (n=21), patients with advanced adenomas (precancerous lesions, n=51), early-stage CRC (Tis-T1, n=24), and advanced CRC (T2-T4, n=53). Levels of the five lncRNAs in plasma were measured by quantitative PCR and normalized to 5S rRNA using the 2^-ΔCt method. Expression trends across the four groups were analyzed. Receiver operating characteristic (ROC) curves (area under the curve, AUC) were generated to assess the ability of individual lncRNAs to distinguish early CRC from controls. A logistic regression model was used to combine multiple lncRNAs into a panel and evaluate its diagnostic performance (sensitivity and specificity).

Results

Bioinformatic analysis identified 12 lncRNAs with stepwise expression changes from adenoma to carcinoma, and the top five candidates were successfully measured in plasma. Among these, UCA1 and SNHG17 showed progressively increasing plasma levels from healthy controls to adenoma to early CRC, with the highest levels in advanced CRC (trend P<0.05). In contrast, CRNDE levels remained unchanged between healthy and early CRC groups but rose significantly in advanced CRC, suggesting its upregulation is associated with tumor progression. The other two lncRNAs (ZFAS1, FOXP4-AS1) exhibited less pronounced changes. In diagnostic tests, UCA1 alone distinguished early-stage CRC from controls with an AUC of 0.82, whereas SNHG17 achieved an AUC of 0.73. Notably, a combined three-lncRNA panel (UCA1 + SNHG17 + CRNDE) improved early CRC detection, achieving an AUC of 0.85 with 87.5% sensitivity and 61.9% specificity for differentiating early CRC from healthy individuals. This multi-marker panel outperformed any single lncRNA biomarker in identifying early CRC.

Conclusion

A GEO dataset-guided approach coupled with plasma validation provided robust evidence that circulating lncRNAs have significant diagnostic potential for CRC. UCA1 and SNHG17 emerged as promising blood-based markers for early detection of colorectal neoplasia, while CRNDE may serve as a complementary marker indicative of advanced disease progression. Moreover, a panel combining these lncRNAs demonstrated superior accuracy over individual markers, underscoring the value of a multi-lncRNA approach. These findings support further development of non-invasive, lncRNA-based blood tests for early colorectal cancer screening.

Introduction

Since currently utilized screening tools including fecal immunochemical test and serum tumor markers cannot reveal sufficient diagnostic powers for colorectal cancer (CRC) due to their low sensitivities. It is thus hopeful to discover non-invasive diagnostic biomarkers for CRC. Urine is one of the most attractive samples for mass-screening because of the non-invasiveness and easy handling. We have previously reported many types of urinary biomarkers for gastrointestinal malignancies.

Aims & Methods

We conducted the current study to discover and establish urinary protein biomarkers that enables early detection of CRC. Among 475 patients including 299 healthy controls (HCs) and 175 stage 0-III CRC patients, age- and sex-matched 373 patients were enrolled in this case-control study. A whole cohort was randomly divided into the discovery cohort (n=32), training cohort (n=220) and validation cohort (n=111). In the discovery cohort, we have performed the isobaric tags for relative and absolute quantitation (iTRAQ) -coupled liquid chromatography-mass spectrometry (LC-MS) to identify urinary protein biomarker candidates. After that, the urinary protein biomarkers were established with ELISA in the training cohort. Finally, the established biomarkers were validated with ELISA in the independent validation cohort.

Results

In the discovery cohort, we identified 78 urinary proteins with aberrant expression between HCs and CRC patients. Among them, urinary levels of 11 proteins were significantly higher in the CRC patients than in the HCs, and 4 urinary proteins were independent biomarkers on the multivariate analysis in the training cohort. In the validation cohort, these urinary proteins also showed significantly higher levels in the CRC patients than in the HCs. Of these urinary biomarkers, DPEP1 and TFF1 were top two urinary protein biomarkers for the diagnosis of CRC, and the combination biomarker panel using these two proteins showed an excellent AUC of 0.870 with 94.3% sensitivity and 63.4% specificity for the diagnosis of stage 0-III CRC. Notably, this combination biomarker panel could distinguish stage 0-I CRC that are curable with endoscopic resection, with an AUC of 0.852, 93.8% sensitivity and 61.6% specificity.

Conclusion

The established novel urinary biomarker panel provides a promising method for early detection of CRC with completely non-invasive manner.

Introduction

Colorectal cancer (CRC) ranks as the third most common cancer globally in both men and women, with a notably higher incidence in developed countries. While early detection, facilitated by screening tools such as the fecal occult blood (FOB) test, has contributed to a decline in mortality rates, CRC continues to pose a significant public health challenge. Meanwhile, extracellular vesicles (EVs), known to be lipid-based particles secreted by cells that carry various macromolecules like nucleic acids and proteins, have emerged as a promising source for the identification of novel fecal biomarkers.

Aims & Methods

Given that FOB testing can produce false positives, often resulting in unnecessary exploratory colonoscopies and placing strain on healthcare resources, the goal of this study is to identify more specific CRC biomarkers within stool-derived EVs to enhance the diagnostic utility of current screening methods. In this study, 20 stool samples were analyzed from individuals categorized as healthy, low-risk, high-risk, or diagnosed with colorectal cancer (CRC). The low-risk group included individuals with one or two adenomatous lesions exhibiting low-grade dysplasia and serrated lesions without dysplasia, all measuring less than 10 mm. The high-risk group comprised individuals with three or more tubular adenomas with low-grade dysplasia under 10 mm, at least one adenoma with a villous component, any lesion with high-grade dysplasia over 10 mm, or at least one serrated lesion either displaying dysplasia or exceeding 10 mm in size.

Results

EVs were isolated using an optimized size exclusion chromatography protocol. Characterization of the EVs was carried out according to the MISEV 2023 guidelines, including analysis of particle size and concentration via Nanoparticle Tracking Analysis (NTA), visualization through transmission electron microscopy (TEM) and atomic force microscopy (AFM), and assessment of the tetraspanins CD9 and CD63.
Following isolation, proteomic profiling of the EVs was performed using liquid chromatography–mass spectrometry (LC-MS), aiming to distinguish protein expression patterns between “normal” individuals (healthy and low-risk) and “discovery” patients (high-risk and CRC cases). A subsequent Gene Set Enrichment Analysis (GSEA) was conducted on differentially expressed proteins to explore associated biological pathways.
The study successfully optimized EV isolation from stool samples, effectively separating vesicles from free proteins. From a total of 484 identified proteins, 75 were more abundant in EVs from discovery patients, while 147 were more prevalent in normal individuals, indicating potential biomarker candidates for CRC detection. Gene Set Enrichment Analysis (GSEA) identified multiple inflammation-related pathways significantly enriched in upregulated proteins from discovery-associated EVs.

Conclusion

In summary, this work demonstrates the potential of fecal EVs as a non-invasive platform for early colorectal cancer detection. By improving diagnostic specificity, this approach may help reduce the number of unnecessary colonoscopies. Future studies will aim to validate these biomarker candidates in larger, more diverse patient cohorts. Acknowledgements: Project PROSALUT2023-4, from the Balearic Islands Government, and CINUIB Fundraising Project (FUEIB).

Introduction

Although the prognostic significance of cellular components of the immune system has been investigated in several solid neoplasms and is well established, the role of plasma cells in the tumor microenvironment has been neglected and only recently these cells are increasingly being appreciated as key players in the tumor microenvironment.

Aims & Methods

The purpose of our study is to explore the contribution of plasma cells to the immune microenvironment of colorectal adenocarcinomas and describe their correlation with prognosis.
In our study, a total of 108 patients with colorectal adenocarcinoma were included [68 men/40 women, median age (IQR): 70 (64-76) years, I-IV stage (AJCC/TNM 8^th edition)] who underwent surgical resection between January 2004 to May 2008. Histological slides and paraffin blocks were retrieved from the archives of the Department of Pathology, Attikon University Hospital. Tissue microarrays (TMAs) of 2 mm diameter were constructed with representative areas from the center and periphery of the tumor. Immunohistochemical stains were performed on TMAs to detect the presence of plasma cells (CD138) and cells of adaptive immunity (CD3, CD4, CD8, CD20). Tertiary lymphoid structures (TLS) were assessed on hematoxylin-eosin-stained slides. Depending on the number of plasma cells, the cases were classified into the following categories: absence of plasma cells or presence of rare single cells, presence of rare small aggregates (>5 cells/aggregation), presence of frequent aggregates, presence of large aggregates or sheets of plasma cells. Clinical and pathologic information was acquired from hospital medical records including patient’s outcome and survival.

Results

Ιncreased number of plasma cells (presence of frequent aggregates, presence of large aggregates or sheets of plasma cells) was observed in 70 cases (65%), while absence or rare aggregates of plasma cells was demonstrated 38 cases (35 %). The presence of large aggregates or sheets of plasma cells in the tumor was significantly associated with the presence of TLS (p=0.004) and tumor infiltration by increased numbers of CD3⁺, CD8⁺ T, and CD20⁺ B lymphocytes compared with the absence of plasma cells or the presence of rare single plasma cells (p=0.025, p=0.012, p=0.001, respectively). Moreover, it was reported that the presence of an increased number of plasma cells compared with the absence of plasma cells in the center of the tumor is significantly correlated to a more favorable prognosis (77 vs 47 months; p=0.047; p<0.05).

Conclusion

In patients with colorectal adenocarcinoma, the presence of high densities of plasma cells in the tumor bed may be associated with increased adaptive immune cell populations in the tumor environment, as well as with longer patient’s survival. Consequently, a careful evaluation of plasma cells and a better understanding of their role in the tumor microenvironment of colorectal cancer seems to be crucial in order to design efficient immunotherapeutic strategies.

References

1.Galon et al. Tumor immunology and tumor evolution: intertwined hisories. Immunity. 2020 Jan 14;52(1):55-81.
2.Hegde et al. Top 10 Challenges in Cancer Immunotherapy. Immunity. 2020 Jan 14;52(1):17-35.