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Targeting undruggable intracellular proteins with peptides: novel on-target macrocyclic peptide inhibitors of KRAS with broad inhibition of proliferation of multiple KRAS-dependent cancer cell lines.

Macrocyclic peptides can disrupt previously intractable protein–protein interactions (PPIs) relevant to oncology targets such as KRAS. Early hits often lack cellular activity and require meticulous improvement of affinity, permeability, and metabolic stability to become viable leads. We have validated the use of the Automated Ligand Identification System (ALIS) to screen oncogenic KRAS G12D (GDP) against mass-encoded mini-libraries of macrocyclic peptides and accelerate our structure–activity relationship (SAR) exploration. These mixture libraries were generated by premixing various unnatural amino acids without the need for the laborious purification of individual peptides. The affinity ranking of the peptide sequences provided SAR-rich data sets that led to the selection of novel potency-enhancing substitutions in our subsequent designs. Additional stability and permeability optimization resulted in the identification of peptide 7 that inhibited pERK activity in a pancreatic cancer cell line. More broadly, this methodology offers an efficient alternative to accelerate the fastidious hit-to-lead optimization of PPI peptide inhibitors.

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Background: Immunotherapy has so far had limited success in colorectal cancer (CRC), with its efficacy restricted to a subset of microsatellite instability high (MSI-H) tumors. A comprehensive interrogation of the CRC tumor immune microenvironment (TME) is urgently needed. We present here an ongoing multi-platform study on early stage colon and rectal cancers, where immuno-genomic profiling of tumors and patient-derived cell models of tumor epithelia, cancer-associated fibroblasts and tumor-infiltrating lymphocytes (TIL) complement each other, with opportunities for mutual cross-validation between experimental and bioprofiling data. Methods: At the time of writing, 21 of a planned 50 early stage CRC patients have been recruited. Surgically resected tumors are processed for 4 broad classes of analyses: 1) Bulk tissue profiling by RNA and whole exome sequencing; 2) High resolution protein and transcriptome analysis comprising scRNA-seq and flow cytometry/CyToF; 3) H&E analysis and multiplex immunohistochemistry for TME-specific proteins; 4) Culture of epithelial, fibroblast, and TIL lines, and generation of patient-derived xenografts for functional studies. Results: Four tumors were MSI-H and 17 were microsatellite stable (MSS), with 1 POLE-mutant MSS patient harboring over 6000 mutations. Bulk genomics analysis revealed the most common mutations to be in TP53, APC, MUC17, and TGFBR2. The most frequently altered pathways were WNT, followed in order by p53, TGFβ, PI3K, and RAS-MAPK. scRNA-seq and flow cytometry/CyToF analyses are being performed to examine immune phenotypes, mediators of cell migration, and immune suppressive populations, which complement data on transcriptomic profile, histopathology, and spatial localization of TME cellular components. Of the 3 cultured cell types, 16 patients have lines of at least one cell compartment established in vitro. Characteristics of individual models will be reported at the meeting. Establishing the 3 cultured cell types from the same patient will enable us to develop an autologous patient-derived co-culture system to evaluate all 3 pairwise interactions, including TIL cytotoxicity toward epithelial cells, mutual modulation by fibroblast and epithelial cells in co-culture and their phenotypic alterations, and fibroblast regulation of TIL cytotoxic function. Autologous co-cultures with all 3 cell types are also planned. Conclusions: The generation of well-annotated multi-platform profiling data from CRC tumors, complemented by matched tri-compartment patient-derived cell cultures, enables mutual cross-validation between experimental models of the TME and bioprofiling data. Citation Format: Lindsay H. Kua, Fiona Y. Lee, Christine L. Eng, Harini Srinivasan, Rahul Nahar, Janice H. Oh, Nicole Ann L. Gunn, Kai Xian Thng, Ashley S. Yong, Adrian C. Sim, Rebecca Lim, Nicole Boo, Simeen Malik, Michael T. Wong, Tze Guan Tan, Shu Wen S. Ho, Shirleen Soh, Wan Jun Lim, Macalinao Dominique Camat, Joe P. Yeong, Clarinda W. Chua, Wei Qiang Leow, Ramanuj DasGupta, Si-Lin Koo, Lewis Hong, Brian Henry, Tony K. Lim, Iain B. Tan. Tri-compartment (epithelial, immune, fibroblast) patient-derived models of the tumor microenvironment from an immuno-genomic profiled cohort of early stage colorectal cancers [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3990.