# ANCHOR Correlative Science Administrative Supplement

> **NIH NIH UM1** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2024 · $649,983

## Abstract

7. Project Summary / Abstract
The ANCHOR Study is an ongoing, longitudinal, multicenter trial in people living with HIV
(PLWH), which demonstrated that treating anal high-grade squamous intraepithelial lesions
(HSIL, or precancer) prevents progression to anal cancer, as compared to active monitoring
(six-monthly high-resolution anoscopy exams with biopsies and cytology). This trial was a
unique opportunity to conduct a randomized study comparing monitoring to treatment, the utility
of which had not yet been established as effective and therefore not considered standard care.
As part of the trial, we collected serial samples to establish a biobank, and therefore a unique
opportunity to conduct comparisons in participants who did and did not progress to cancer. Our
aims with this supplement are to initiate the trial’s correlative science objectives to inform HSIL
screening algorithms for secondary prevention of anal cancer, optimize use of HRA and HSIL
treatment resources by identifying biomarkers of HSIL regression, and explore the molecular
pathogenesis of progression from HSIL to anal cancer. Findings from this research, among
other assays, are intended to inform optimal screening and treatment strategies for anal cancer
prevention in PLWH and potentially other groups.

## Key facts

- **NIH application ID:** 10923413
- **Project number:** 3UM1CA121947-17S1
- **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- **Principal Investigator:** Joseph A. Sparano
- **Activity code:** UM1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $649,983
- **Award type:** 3
- **Project period:** 2024-04-01 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10923413

## Citation

> US National Institutes of Health, RePORTER application 10923413, ANCHOR Correlative Science Administrative Supplement (3UM1CA121947-17S1). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10923413. Licensed CC0.

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