Immunotherapy (IO) for patients with (NSCLC) has emerged as a main treatment option, both for early-stage and late-stage NSCLC. PD-L1 expression by IHC is the used predictive biomarker and most validated. Patients with early-stage NSCLC (non-EGFR) will be offered adjuvant IO therapy. TMB is another potential biomarker for IO therapy, but its role in NSCLC is still not clear. Future predictive biomarkers or combinations will be discussed.

Interrogation of matched blood and biopsy specimens from anti-PD1 treated patients has identified peripheral biomarkers of clinical response closely reflecting correlates found in the TME. Specifically, AI analyses of blood flow-cytometry revealed subsets of PD1+ T cells predictive of response correlating with cells found in the TME. We also identify plasma signatures predictive of response also found predictive in the TME, highlighting the benefit of peripheral assays to ascertain TME.

Extracellular vesicles (EVs) found in all body fluids play a key role in health and disease, including cancer. Tumor-derived exosomes (TEX) mimic the content of parent tumor cells and thus serve as surrogates of tumor cells in “liquid biopsy.” We separated TEX from non-TEX in plasma of cancer patients by immune capture with Abs to the tumor- or T cell- associated antigens and studied the proteomes of both fractions using high resolution mass spectrometry (HRMS). Simultaneous analysis of TEX and T-cell derived CD3+non-TEX in the same cancer plasma samples showed that exosomes (sEV) have a potential to serve as liquid biomarkers of tumor progression.

Historically, cancer drugs are combined orthogonally to overcome resistance. “Independent Action” mathematically tests this approach. In the immuno-oncology (IO) era, efforts to rationally design combinations have led to a surge of trials proposing “synergy.” The failure of scientists to understand pharmacologic synergy may be contributing to increasing futility in moving cancer drugs from Phase 1 to registration. Clinical “synergy” is very rare in drug development, especially in IO combinations.       

The genomic revolution has demonstrated that targeted drugs, in order to be useful, must be given to patients whose tumors bear the cognate target. For instance, EGFR kinase inhibitors are active against cancers with EGFR kinase mutations, but inactive against cancers without the targeted alteration. Similarly, optimizing immunotherapy will require a precision approach, i.e., identification of malignancies that harbor an immune target modifiable by the specific immunotherapy given.

Blocking either the PD-1 receptor or its ligand PD-L1 has improved overall survival in Phase III trials in patients across tumor types. While some tumors fail to response due to a lack of immune cells infiltrating the tumor, others fail despite immune cells in the tumor. The microenvironment of many “hot” tumors is hostile to antitumor lymphocyte activity, in part due to the innate immune system, including myeloid cell populations and NK cells. By targeting these innate immune cells via pathways such as CSFR1 or HHLA2, we may be able to improve the responses and durable outcomes of PD-1/PD-L1 therapy for patients with these “hot” tumors.

We have recently found that defects of the replication stress response (RSRD) may enhance the immunogenicity of TNBC and therefore its responsiveness to ICT. TNBC cells expressing high levels of an RSRD gene signature accumulate cytoplasmic DNA and induce immunostimulatory cytokine production, which is required for the effectiveness of ICT. Intriguingly, the RSRD gene signature score correlated perfectly with the response of TNBC to ICT in syngeneic mouse models and patient cohorts. All these intriguing findings strongly suggest that RSRD acts as a key determinant of ICT outcomes in TNBC, and that RSRD-enhancing drugs may sensitize ICT-resistant TNBC to immunotherapy.

There are many examples of tissue-derived prognostic and predictive biomarkers. In oncology, these markers inform patients of expected outcomes. Oncology biomarkers drive the treatment algorithms to the point physicians need DNA and protein results to make a basic therapeutic plan. This lecture will demonstrate the importance of biomarkers in the practice of oncology and how these additional markers can be uncovered. The focus is on human tissue as a platform for biomarker use and discovery. 

One form of the most successful cellular immunotherapies (isolating subsets of white blood cells, engineering them to express chimeric antigen receptors [CARs] that recognize tumor proteins, and re-infusing them back into the patient) for cancer patients is a promising treatment option for many types of blood cancer. To work well, CAR-modified cells must form an effective immune synapse (IS, also known as the “kiss of death”) with susceptible tumor cells (no synapse, no killing), which reflects both the therapeutic CAR immune cell and its tumor cell target.

Multiplexed immune cell profiling of the tumor microenvironment (TME) has improved our understanding of cancer immunology. We have used imaging mass cytometry (IMC) to characterize the tumor and immune cell architecture of aggressive lymphoma. We integrate tumor mutational profiling, clinical outcomes, and multiplexed immuno-phenotyping of the TME into a spatial analysis of lymphoma at the single cell level and identify candidate biomarkers for treatment response.

Cellular “maps” shed light on the spatial regulation mechanisms of many disorders. The next challenge in spatial biology is to link the cellular function to the cell phenotypes in their environments. Image-based multiparameter molecular profiling has the potential to decode high-dimensional dynamics of signaling and metabolism at the subcellular and molecular level in complex tissues and organs. In this talk, I will introduce multiplex imaging modalities (genomics, proteomics, and metabolomics) to decipher the spatial and temporal decision-making of single-cells at macromolecular resolution in engineered organoids and human tissues for systems immuno-engineering, subcellular precision oncology, and personalized regenerative medicine applications.