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1. Joint modeling HIV and HPV using a new hybrid agent-based network and compartmental simulation technique

   https://doi.org/10.1371/journal.pone.0288141  

   Zhao, Xinmeng; Gopalappa, Chaitra (November 2023, PLOS ONE)

   Kolawole, Olatunji Matthew (Ed.)

   Persons living with human immunodeficiency virus (HIV) have a disproportionately higher burden of human papillomavirus infection (HPV)-related cancers. Causal factors include both behavioral and biological. While pharmaceutical and care support interventions help address biological risk of coinfection, as social conditions are common drivers of behaviors, structural interventions are key part of behavioral interventions. Our objective is to develop a joint HIV-HPV model to evaluate the contribution of each factor, to subsequently inform intervention analyses. While compartmental modeling is sufficient for faster spreading HPV, network modeling is suitable for slower spreading HIV. However, using network modeling for jointly modeling HIV and HPV can generate computational complexities given their vastly varying disease epidemiology and disease burden across sub-population groups. We applied a recently developed mixed agent-based compartmental (MAC) simulation technique, which simulates persons with at least one slower spreading disease and their immediate contacts as agents in a network, and all other persons including those with faster spreading diseases in a compartmental model, with an evolving contact network algorithm maintaining the dynamics between the two models. We simulated HIV and HPV in the U.S. among heterosexual female, heterosexual male, and men who have sex with men (men only and men and women) (MSM), sub-populations that mix but have varying HIV burden, and cervical cancer among women. We conducted numerical analyses to evaluate the contribution of behavioral and biological factors to risk of cervical cancer among women with HIV. The model outputs for HIV, HPV, and cervical cancer compared well with surveillance estimates. Model estimates for relative prevalence of HPV (1.67 times) and relative incidence of cervical cancer (3.6 times), among women with HIV compared to women without, were also similar to that reported in observational studies in the literature. The fraction attributed to biological factors ranged from 22–38% for increased HPV prevalence and 80% for increased cervical cancer incidence, the remaining attributed to behavioral. The attribution of both behavioral and biological factors to increased HPV prevalence and cervical cancer incidence suggest the need for behavioral, structural, and pharmaceutical interventions. Validity of model results related to both individual and joint disease metrics serves as proof-of-concept of the MAC simulation technique. Understanding the contribution of behavioral and biological factors of risk helps inform interventions. Future work can expand the model to simulate sexual and care behaviors as functions of social conditions to jointly evaluate behavioral, structural, and pharmaceutical interventions for HIV and cervical cancer prevention. 

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2. Abstract 7077: Immunofluorescence microtissue array (IMA) for detection of prognostic cancer stem cell biomarkers

   https://doi.org/10.1158/1538-7445.AM2025-7077  

   Das, Madhumita; Henry, Kymkecia; Armstrong, Djarie; Truman, Charle; Kendrick, Charlie; Saunders, Maya S; Anderson, Juan E; Lovett, Malcolm J; Stiffin, Rose; Huisso, Ayivi; et al (April 2025, Cancer Research)

   AACR (Ed.)

   Abstract Cancer is an intricate disease accountable for the deaths of over 10 million people per year in the United States of America. Several scientific studies showed that the cancer stem cell (CSC) markers have prognostic significance in various cancers and are crucial for designing anticancer drugs to lower cancer death. However, there was a lack of rapid, accurate identification, and analysis, of the prognostic cancer stem cell (CSC) biomarkers in numerous cancer patients. In our laboratory, we identified and analyzed prognostic lung cancer stem cell markers (LCSCs) by using the Immunofluorescence microtissue array (IMA) technique in different lung cancer patient’s tissue biopsy samples and observed that the increased expression of LCSCs principally, CD44 and CD80 in stage IIIA lung cancer tissues compared to normal lung biopsy tissues. We also investigated pancreatic cancer stem cell biomarkers (PAN CSCs) namely CD44 and CD80 with the IMA technique in pancreatic biopsy tissues. The CD44 fluorescence proved an increased expression in adenocarcinoma pancreatic cell tissues when compared to CD80. We also studied and analyzed the stage progression with ovarian cancer stem cell biomarkers (OCSCs) chiefly CD54 and CD44 using the IMA technique in ovarian cancer patients and normal biopsy tissues. The increased expression of CD44 and CD54 were observed in Stage III ovarian cancer tissues compared to normal ovarian tissue indicating the potential role of these OCSC’s biomarkers for the prognosis of ovarian cancer pathogenesis. Our results of prognostic cancer stem cell biomarkers of lung, pancreatic, and ovarian cancers have been analyzed by one-way ANOVA and bioinformatics software (Reactome, Cytoscape PSICQUIC services, STRING) to find underlying molecular mechanism of target gene regulation of increased expression of prognostic CSCs which may give a clue for the prevention and treatment of these cancers. Further research is warranted for these lung, pancreatic, and ovarian CSCs which could be valuable for clinical trials and drug discovery against these CSC biomarkers at early-stage development. Citation Format:Madhumita Das, Kymkecia Henry, Djarie Armstrong, Charle Truman, Charlie Kendrick, Maya S. Saunders, Juan E. Anderson, Malcolm J. Lovett, Rose Stiffin, Ayivi Huisso, Donrie Purcell, Marco Ruiz, Paulo Chaves, Jayanta Kumar Das. Immunofluorescence microtissue array (IMA) for detection of prognostic cancer stem cell biomarkers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7077. 

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3. Spatially-aware clustering improves AJCC-8 risk stratification performance in oropharyngeal carcinomas

   https://doi.org/10.1016/j.oraloncology.2023.106460  

   Canahuate, Guadalupe; Wentzel, Andrew; Mohamed, Abdallah SR; van_Dijk, Lisanne V; Vock, David M; Elgohari, Baher; Elhalawani, Hesham; Fuller, Clifton D; Marai, G Elisabeta (September 2023, Oral Oncology)

   Objective: Evaluate the effectiveness of machine learning tools that incorporate spatial information such as disease location and lymph node metastatic patterns-of-spread, for prediction of survival and toxicity in HPV+ oropharyngeal cancer (OPC). Materials & methods: 675 HPV+ OPC patients that were treated at MD Anderson Cancer Center between 2005 and 2013 with curative intent IMRT were retrospectively collected under IRB approval. Risk stratifications incorporating patient radiometric data and lymph node metastasis patterns via an anatomically-adjacent representation with hierarchical clustering were identified. These clusterings were combined into a 3-level patient stratification and included along with other known clinical features in a Cox model for predicting survival outcomes, and logistic regression for toxicity, using independent subsets for training and validation. Results: Four groups were identified and combined into a 3-level stratification. The inclusion of patient stratifications in predictive models for 5-yr Overall survival (OS), 5-year recurrence free survival, (RFS) and Radiation-associated dysphagia (RAD) consistently improved model performance measured using the area under the curve (AUC). Test set AUC improvements over models with clinical covariates, was 9 % for predicting OS, and 18 % for predicting RFS, and 7 % for predicting RAD. For models with both clinical and AJCC covariates, AUC improvement was 7 %, 9 %, and 2 % for OS, RFS, and RAD, respectively. Conclusion: Including data-driven patient stratifications considerably improve prognosis for survival and toxicity outcomes over the performance achieved by clinical staging and clinical covariates alone. These stratifications generalize well to across cohorts, and sufficient information for reproducing these clusters is included. 

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4. Evaluating Risk-Stratified HPV Catch-up Vaccination Strategies: Should We Go beyond Age 26?

   https://doi.org/10.1177/0272989X211042894  

   Wang, Fan; Jozkowski, Kristen N.; Zhang, Shengfan (May 2022, Medical Decision Making)

   Background Human papillomavirus (HPV) is the most common sexually transmitted infection in the United States. HPV can cause genital warts and multiple types of cancers in females. HPV vaccination is recommended to youth age 11 or 12 years before sexual initiation to prevent onset of HPV-related diseases. For females who have not been vaccinated previously, catch-up vaccines are recommended through age 26. The extent to which catch-up vaccines are beneficial in terms of disease prevention and cost-effectiveness is questionable given that some women may have been exposed to HPV before receiving the catch-up vaccination. This study aims to examine whether the cutoff age of catch-up vaccination should be determined based on an individual woman’s risk characteristic instead of a one-size-fits-all age 26. Methods We developed a microsimulation model to evaluate multiple clinical outcomes of HPV vaccination for different women based on a number of personal attributes. We modeled the impact of HPV vaccination at different ages on every woman and tracked her course of life to estimate the clinical outcomes that resulted from receiving vaccines. As the simulation model is risk stratified, we used extreme gradient boosting to build an HPV risk model estimating every woman’s dynamic HPV risk over time for the lifetime simulation model. Results Our study shows that catch-up vaccines still benefit all women after age 26 from the perspective of clinical outcomes. Women facing high risk of HPV infection are expected to gain more health benefits compared with women with low HPV risk. Conclusions From a cancer prevention perspective, this study suggests that the catch-up vaccine after age 26 should be deliberately considered. 

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5. HPV-EM: an accurate HPV detection and genotyping EM algorithm

   https://doi.org/10.1038/s41598-020-71300-7  

   Inkman, Matthew J.; Jayachandran, Kay; Ellis, Thomas M.; Ruiz, Fiona; McLellan, Michael D.; Miller, Christopher A.; Wu, Yufeng; Ojesina, Akinyemi I.; Schwarz, Julie K.; Zhang, Jin (August 2020, Scientific Reports)

   Abstract Accurate HPV genotyping is crucial in facilitating epidemiology studies, vaccine trials, and HPV-related cancer research. Contemporary HPV genotyping assays only detect < 25% of all known HPV genotypes and are not accurate for low-risk or mixed HPV genotypes. Current genomic HPV genotyping algorithms use a simple read-alignment and filtering strategy that has difficulty handling repeats and homology sequences. Therefore, we have developed an optimized expectation–maximization algorithm, designated HPV-EM, to address the ambiguities caused by repetitive sequencing reads. HPV-EM achieved 97–100% accuracy when benchmarked using cell line data and TCGA cervical cancer data. We also validated HPV-EM using DNA tiling data on an institutional cervical cancer cohort (96.5% accuracy). Using HPV-EM, we demonstrated HPV genotypic differences in recurrence and patient outcomes in cervical and head and neck cancers. 

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