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87


Machine Learning as an Answer to the Mass-Forming DCIS Conundrum: A Pilot Study [Meeting Abstract]

Hacking, Sean; Ben Khadra, Shaza; Siddique, Ayesha; Singh, Kamaljeet; Taliano, Ross; Yakirevich, Evgeny; Wang, Yihong
ISI:000770360200116
ISSN: 0023-6837
CID: 5516292

Oral administration of TRAIL-inducing small molecule ONC201/TIC10 prevents intestinal polyposis in the Apc min/+ mouse model

Madka, Venkateshwar; De La Cruz, Arielle; Pathuri, Gopal; Panneerselvam, Janani; Zhang, Yuting; Stratton, Nicole; Hacking, Sean; Finnberg, Niklas K; Safran, Howard P; Sei, Shizuko; Glaze, Elizabeth R; Shoemaker, Robert; Fox, Jennifer T; Raufi, Alexander G; El-Deiry, Wafik S; Rao, Chinthalapally V
Colorectal cancer (CRC) incidence is rising globally. Hence, preventing this disease is a high priority. With this aim, we determined the CRC prevention potential of the TRAIL-inducing small molecule ONC201/TIC10 using a preclinical model representing high-risk familial adenomatous polyposis (FAP) patients, Apc min/+ mice. Prior to the efficacy study, optimal and non-toxic doses of ONC201 were determined by testing five different doses of ONC201 (0-100 mg/kg body weight (BW); twice weekly by oral gavage) in C57BL/6J mice (n=6/group) for 6 weeks. BW gain, organ weights and histopathology, blood profiling, and the plasma liver enzyme profile suggested no toxicities of ONC201 at doses up to 100 mg/kg BW. For efficacy determination, beginning at six weeks of age, groups of Apc min/+ male and female mice (n≥20) treated with colon carcinogen azoxymethane (AOM) (AOM-Apc min/+) were administered ONC201 (0, 25, and 50 mg/kg BW) as above up to 20 weeks of age. At termination, efficacy was determined by comparing the incidence and multiplicity of intestinal tumors between vehicle- and drug-treated groups. ONC201 showed a strong suppressive effect against the development of both large and small intestinal tumors in male and female mice. Apc min/+ mice treated with ONC201 (50 mg/kg BW) showed >50% less colonic tumor incidence (P<0.0002) than controls. Colonic tumor multiplicity was also significantly reduced by 68% in male mice (0.44 ± 0.11 in treated vs. 1.4 ± 0.14 in controls; P<0.0001) and by 75% in female mice (0.30 ± 0.10 in treated vs. 1.19 ± 0.19 in controls; P<0.0003) with ONC201 treatment (50 mg/kg BW). Small intestinal polyps were reduced by 68% in male mice (11.40 ± 1.19 in treated vs. 36.08 ± 2.62 in controls; P<0.0001) and female mice (9.65 ± 1.15 in treated vs. 29.24 ± 2.51 in controls; P<0.0001). Molecular analysis of the tumors suggested an increase in TRAIL, DR5, cleaved caspases 3/7/8, Fas-associated death domain protein (FADD), and p21 (WAF1) in response to drug treatment. Serum analysis indicated a decrease in pro-inflammatory serum biomarkers, such as IL1β, IL6, TNFα, G-CSF, and GM-CSF, in the ONC201-treated mice compared with controls. Our data demonstrated excellent chemopreventive potential of orally administered ONC201 against intestinal tumorigenesis in the AOM-Apc min/+ mouse model.
PMCID:9185612
PMID: 35693092
ISSN: 2156-6976
CID: 5516012

A Novel Superpixel Approach to the Tumoral Microenvironment in Colorectal Cancer

Hacking, Sean M; Wu, Dongling; Alexis, Claudine; Nasim, Mansoor
Colorectal cancer (CRC) is the most common malignancy of the gastrointestinal tract. The stroma and the tumoral microenvironment (TME) represent ecosystem-like biological networks and are new frontiers in CRC. The present study demonstrates the use of a novel machine learning-based superpixel approach for whole slide images to unravel this biology. Findings of significance include the association of low proportionated stromal area, high immature stromal percentage, and high myxoid stromal ratio (MSR) with worse prognostic outcomes in CRC. Overall, stromal computational markers outperformed all others at predicting clinical outcomes. MSR may be able to prognosticate patients independent of pathological stage, representing an optimal way to effectively prognosticate CRC patients which circumvents the need for more extensive molecular and/or computational profiling. The superpixel approaches to the TME demonstrated here can be performed by a trained pathologist and recorded during synoptic cancer reporting with appropriate quality assurance. Future clinical trials will have the ultimate say in determining whether we can better tailor the need for adjuvant therapy in patients with CRC.
PMCID:8855322
PMID: 35223135
ISSN: 2229-5089
CID: 5264012

Mass-Forming Ductal Carcinoma in Situ: An Ultrasonographic and Histopathologic Correlation [Meeting Abstract]

Ben Khadra, Shaza; Hacking, Sean; Singh, Kamaljeet; Carpentier, Bianca; Wang, Li Juan; Yakirevich, Evgeny; Wang, Yihong
ISI:000770360200089
ISSN: 0023-6837
CID: 5516272

Increased tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) expression in normal colonic mucosa with imipridone ONC201/TIC10 treatment: A potential biomarker for chemoprevention studies [Meeting Abstract]

Raufi, Alexander G.; De La Cruz, Arielle; George, Andrew; Hacking, Sean; Madka, Venkateshwar; Prabhu, Varun; Safran, Howard; Zhou, Lanlan; Brenner, Dean; Rao, Chinthalapally V.; El-Deiry, Wafik S.
ISI:000892509507044
ISSN: 0008-5472
CID: 5516392

Applied Machine Learning Based on Superpixels and the Tumoral Microenvironment is a Significant Predictor of Neoadjuvant Response in Triple Negative Breast Cancer [Meeting Abstract]

Hacking, Sean; Siddique, Ayesha; Singh, Kamaljeet; Taliano, Ross; Yakirevich, Evgeny; Wang, Yihong
ISI:000770360200115
ISSN: 0023-6837
CID: 5516282

Machine Learning as an Answer to the Mass-Forming DCIS Conundrum: A Pilot Study [Meeting Abstract]

Hacking, Sean; Ben Khadra, Shaza; Siddique, Ayesha; Singh, Kamaljeet; Taliano, Ross; Yakirevich, Evgeny; Wang, Yihong
ISI:000770361800117
ISSN: 0893-3952
CID: 5516342

Applied Machine Learning Based on Superpixels and the Tumoral Microenvironment is a Significant Predictor of Neoadjuvant Response in Triple Negative Breast Cancer [Meeting Abstract]

Hacking, Sean; Siddique, Ayesha; Singh, Kamaljeet; Taliano, Ross; Yakirevich, Evgeny; Wang, Yihong
ISI:000770361800116
ISSN: 0893-3952
CID: 5516332

Mass-Forming Ductal Carcinoma in Situ: An Ultrasonographic and Histopathologic Correlation [Meeting Abstract]

Ben Khadra, Shaza; Hacking, Sean; Singh, Kamaljeet; Carpentier, Bianca; Wang, Li Juan; Yakirevich, Evgeny; Wang, Yihong
ISI:000770361800090
ISSN: 0893-3952
CID: 5516322

HPV-related Adenocarcinoma of the Anorectum is a Rare Mimicker of Rectal Villous Adenomas: A Retrospective Single-center Series [Meeting Abstract]

Siddique, Ayesha; Wu, Elizabeth; Yang, Dongfang; Hacking, Sean; Yakirevich, Evgeny
ISI:000770360201114
ISSN: 0023-6837
CID: 5516312