Identification And Prognostic Prediction Model Studying Of Prognostic Long Non-coding RNA Molecular Markers In Cancer

Abdominal tumors refer to tumors that grow in the abdominal region of the body,including the colon,ovaries,kidneys,small intestine,peritoneum,liver,stomach,and a range of tissues and organs located in the abdomen.Among abdominal tumors,ovarian cancer and colorectal cancer are respectively gynecological malignant tumors with the highest mortality rate and digestive tract tumors with the highest incidence rate.Due to the lack of typical symptoms,most ovarian cancer patients are diagnosed at an advanced stage,leading to a poor prognosis.Colorectal cancer is a highly heterogeneous cancer,with its global incidence and mortality rates continuously increasing.The poor prognosis for colorectal cancer possibly due to its rapid progression and current limitations of modern clinical treatment.Therefore,this study aims to find more appropriate tumor prognostic markers to improve clinical treatment and prognosis for cancer patients.Cancer immunity plays a significant role throughout the development and evolution of cancer.As a crucial process in tumor biology,it relies on a diverse range of immune cells.Furthermore,some studies have revealed the crosstalk between different cell death mechanisms and anti-tumor immunity,such as ferroptosis participating in and affecting tumor immunity through multiple mechanisms,thereby influencing the occurrence and development of tumors.Inducing ferroptosis combined with immune therapy has shown synergistic and enhanced anti-tumor activity.Long non-coding RNAs(lncRNAs)have been found to participate in a wide range of biological processes,and many studies have found that lncRNAs participate in the regulation of tumor cell ferroptosis and immune cell infiltration.Based on the important role of lncRNAs,screening tumor prognostic markers from ferroptosis and tumor immune infiltration-related lncRNAs would be a potential and feasible research direction.Firstly,this study used the ferroptosis-related mRNAs in the FerrDb database to screen out ferroptosis-related lncRNAs through Pearson correlation analysis,and then selected prognostic markers for ovarian cancer by machine learning methods such as Cox regression and LASSO regression.After validating the markers by cell experiments,multivariate Cox regression was used to construct the prognostic prediction signature for ovarian cancer.At the same time,this study also explored the immune cell housekeeping lncRNAs and screened out tumor immune infiltration-related lncRNAs using gene chip data from purified immune cell lines and colorectal cancer cell lines.Prognostic markers for colorectal cancer were selected by machine learning methods such as Cox regression and LASSO regression.After validating the markers by cell experiments,multivariate Cox regression was used to construct the prognostic prediction signature for colorectal cancer.Finally,the two prediction signatures constructed in this study showed good predictive performance in time-dependent ROC curves and predictive nomogram respectively in their training sets and validation sets.Further bioinformatics analysis also confirmed the reliability of the signatures,indicating that the prognostic signatures for colorectal and ovarian cancer constructed in this study can provide a certain reference value for clinical treatment and help further improve patient prognosis.