Table 1.

Challenges for Cancer Immunotherapy¹–⁵,⁸,⁹,¹²,¹⁴,¹⁶,²³,²⁴,²⁶,²⁷,³⁰,³¹,³⁷

Problem	Challenge	Solution
Unpredictable Efficacy
Cancer immunotherapies are effective only in subsets of patients with select cancers	Unknown cancer biomarkers/pathways Tumor heterogeneity Immunosuppressive cancer biology Immunotherapies not given as first-line treatments	Further characterize cancer immunobiology Identify additional genetic mutations, biomarkers, and cancer pathways Identify drug combinations that target multiple mutations Conduct clinical trials to gather efficacy/toxicity data versus SOC agents to gain first-line indication
Biomarker Identification
Difficulty identifying clinically significant biomarkers among the increasing number of genetic mutations detected across tumor types	Technical obstacles Management of large data sets Interpretation of clinical significance of data Economic costs for data analysis	Identify targetable tumor antigens Investigate tumor antigens expressed by CSCs Routinely apply NGS technologies for cancer biomarker screening Maintain publicly available database(s) of clinical significance/actionability of genetic mutations
Need to identify more predictive biomarkers for cancer immunotherapies	Few robustly validated predictive biomarkers Technical challenges in identifying predictive genetic mutations Difficulty identifying patients who will/won’t respond to treatment	Identify and validate additional biomarkers with predictive value Foster collaboration between multidisciplinary teams of experts on biomarker data and interpretation Use high-throughput NGS technologies routinely to screen patients for predictive biomarkers Maintain publicly available database(s) of clinical significance of predictive biomarkers
Tumor Heterogeneity
High level of heterogeneity found in tumor and metastatic lesion genetic mutations	Efficacy impeded due to variability in target mutations	Biopsy tumors in patients with disease progression to identify targetable mutations Personalize treatment using liquid biopsies to characterize tumor heterogeneity Use drug combinations as first-line treatment
Acquired Treatment Resistance
Emergence of resistance to single-target cancer immunotherapy treatments	Contributes to therapeutic failure in clinical practice Potential toxicity of combination therapies to combat resistance	Identify and target resistant tumor cell subclones Develop low-toxicity drug combination treatments to bypass or prevent resistance Take pre- and post-treatment tumor biopsies to identify and target mutations causing relapse Combine drugs or other treatments to overcome resistance
Clinical Trial Design
Distinct clinical criteria needed for cancer immunotherapy evaluation	Traditional clinical trial design doesn’t detect important endpoints for immunotherapies	Design clinical trials that incorporate extended endpoints and other immune-related criteria
Low prevalence of some biomarkers in patient cohorts	Large, multi-institutional clinical trials required Long recruitment period increases time and costs	Optimize patient biomarker prescreening methods Design biomarker-driven trials to evaluate clinical efficacy in small patient cohorts Prioritize molecular targets
Cost
Cancer immunotherapy drugs are expensive	Exerts economic strain on health care system and patient finances High cost limits patient access	Routinely screen patients for predictive biomarkers that indicate who will/won’t respond to treatment Use cost-effectiveness, cost–benefit, and QoL assessments to evaluate relationship between clinical benefit and treatment cost Develop novel drug reimbursement modalities Use immunoprevention strategies to reduce cancer treatment costs

CSCs = cancer stem cells; NGS = next-generation sequencing; QoL = quality of life; SOC = standard of care.