Human papillomavirus (HPV) has long been recognized for causing benign lesions such as warts, but its pivotal role in cancer was established in the late 20th century, culminating in the 2008 Nobel Prize awarded to Harald zur Hausen for linking HPV to cervical cancer

Treatment-refractory rectal cancer liver metastasis represents a major therapeutic challenge, particularly in the absence of actionable genomic biomarkers. Functional precision oncology approaches integrating genomic profiling with patient-derived organoid (PDO) drug testing may provide biologically informed therapeutic prioritization. A 50-year-old female patient with KRAS/TP53-mutant, microsatellite-stable (MSS) rectal adenocarcinoma refractory to FOLFIRINOX was enrolled. A liver metastasis from a treatment-refractory rectal cancer patient was processed to establish three-dimensional patient-derived organoids. Histopathological concordance was assessed using H&E and p53 immunohistochemistry. Comprehensive genomic profiling was performed using a 637-gene targeted next-generation sequencing panel, enabling detection of single-nucleotide variants, indels, copy number variations, microsatellite instability, and tumor mutational burden. Functional drug sensitivity profiling was conducted in parallel 2D and 3D platforms using a customized 17-agent panel, followed by exploratory combinatorial validation. The organoids demonstrated high phenotypic and genomic concordance with the parental tumor, preserving key driver alterations (KRAS^A146T, TP53^R175H, APC frameshifts, CCNE1 amplification), microsatellite stability, and low tumor mutational burden (TMB: 6.37 mut/Mb). Functional screening identified selective sensitivity to bevacizumab (IC₅₀: 0.130 μM), doxorubicin (IC₅₀: 0.570 μM), carboplatin (IC₅₀: 0.950 μM), and topotecan (IC₅₀: 1.600 μM) in the 3D organoid model, with consistent cross-platform validation. An exploratory combination assay further supported enhanced viability suppression under bevacizumab-based regimens. Critically, at the time of manuscript preparation, the patient demonstrated radiological disease stabilization under bevacizumab plus trastuzumab deruxtecan, consistent with the organoid-derived response profile. These findings highlight the capacity of integrated genomic and organoid-based profiling to uncover therapeutic vulnerabilities beyond standard biomarker assessment. This proof-of-concept case report study demonstrates the feasibility and translational relevance of an established organoid-based functional precision oncology platform for therapeutic prioritization in metastatic rectal cancer.

It has been shown that Human papillomavirus (HPV) infection is associated with several forms of cancer. Additionally, although there are more than 100 types of HPV, more than ten types of it, including types 16 and 18, are considered high-risk. The two proteins that make up the viral capsid of HPV 16 are L1, the major capsid protein, and L2, the minor capsid protein. FDA (The Food and Drug Administration) approved HPV vaccines mostly target L1 and L2 capsid proteins, which facilitate intracellular entry during infection. In this study, it was set out to analyze the creation of phylogenetic relations of L1 nucleic acid sequences of viral isolates. This study also analyzed sequences of three key elements within the amino acid sequences of HPV 16 L1: loops critical for structural stability, nuclear localization signal sequences, and residues implicated in viral attachment. As highlighted by the literature, these elements represent pivotal aspects of viral function. Furthermore, the report highlighted the particular inter-sequence variability within the HPV 16 L1 protein sequences. Overall analysis revealed clustering of sequences primarily due to geographical and characterized by more phylogenetic relatedness within location-specific clusters.

The focus was on developing machine learning models to predict the IC50 values of the compound OTX015 using gene expression levels of cancer cell lines. Through regression-based machine learning models, particularly the SVM model, trained on pre-laboratory data, consistent and generalizable performance with low error scores was achieved. These models underwent enhancement via hyperparameter optimization and were tested on validation data. The results indicate the utility of machine learning in drug discovery processes and personalized medicine, offering rapid and cost-effective predictions of IC50 values. However, for enhanced reliability, further model development, data gathering, and evaluation with diverse compounds are recommended. In conclusion, this research demonstrates the potential of machine learning approaches to optimize experimental processes, reduce costs, and contribute to personalized treatments in healthcare by accurately predicting compound responses.

Background/Objectives: Cancer remains a leading cause of mortality worldwide, creating a persistent clinical need for accurate and minimally invasive approaches capable of detecting malignancy at earlier and more treatable stages. Circulating cell-free DNA (cfDNA) has emerged as a transformative liquid-biopsy analyte that provides information beyond somatic mutation detection. This review examines three complementary dimensions of cfDNA analysis-fragmentomics, methylomics, and CRISPR-enabled biosensing-and evaluates their potential roles in cancer detection, classification, and monitoring. Methods: This narrative review synthesizes current evidence on cfDNA fragmentomic features, including fragment size distribution, end motifs, jagged ends, nucleosome footprinting, orientation-aware fragmentation, and machine-learning-based classification. It also reviews bisulfite-based and bisulfite-free methylation profiling, multi-cancer early detection strategies, nanopore-based methylation analysis, and CRISPR-Cas systems adapted for sequence- and methylation-sensitive nucleic acid biosensing. Results: Fragmentomic approaches exploit structural characteristics of cfDNA that reflect chromatin organization, nuclease activity, and tissue of origin, while methylomic analyses provide highly tissue-specific epigenetic information relevant to early cancer detection and tumor localization. CRISPR-Cas12a-, Cas13a-, and related platforms provide programmable, highly specific detection of nucleic acid variants and selected epigenetic modifications with potential for rapid and instrument-minimal testing. Clinical applications across colorectal, lung, breast, hepatocellular, pancreatic, gastric, esophageal, and bladder cancers demonstrate complementary roles for these approaches in early detection, minimal residual disease monitoring, relapse detection, and treatment-response assessment. Conclusions: Fragmentomics, methylomics, and CRISPR-enabled biosensing represent complementary rather than interchangeable strategies for cfDNA analysis. Their broader clinical integration will depend on analytical standardization, prospective validation in diverse populations, improved sensitivity at low tumor fractions, and resolution of regulatory and implementation challenges.

Cervical cancer presents a significant global health concern with high-risk human papilloma-viruses (HPVs) being identified as the cause of this cancer. Although current treatment methods for cervical cancer can eliminate lesions, preventing metastatic spread and minimizing tissue damage remains a major challenge. Therefore, the development of a safer and innovative thera-peutic approach is of utmost importance. Natural products like Fig latex, derived from the Ficus Carica tree, have demonstrated promising anti-cancer properties when tested on cervical cancer cell lines. However, the specific mechanisms by which Fig latex exerts its effects are still un-known. In this study, we conducted RNA-seq analysis to explore how Fig latex may counteract carcinogenesis in HPV-positive cervical cancer cell lines, namely CaSki (HPV type 16-positive) and HeLa (HPV type 18-positive). Our data from this investigation indicates that Fig latex influ-ences the expression of genes associated with the development and progression of cervical can-cer, including pathways related to " Nonsense-Mediated Decay (NMD) "cell cycle regulation" and Transcriptional Regulation by TP53. This selective impact of Fig latex on cancer-related pathways suggests a potential novel therapeutic approach for HPV-related cervical cancer.