RESILIENT Part 2: A Randomized, Open-Label Phase III Study of Liposomal Irinotecan Versus Topotecan in Adults With Relapsed Small Cell Lung Cancer

PURPOSE The phase III RESILIENT trial compared second-line liposomal irinotecan with topotecan in patients with small cell lung cancer (SCLC). PATIENTS AND METHODS Patients with SCLC and progression on or after first-line platinum-based chemotherapy were randomly assigned (1:1) to intravenous (IV) liposomal irinotecan (70 mg/m(2) every 2 weeks in a 6-week cycle) or IV topotecan (1.5 mg/m(2) daily for 5 consecutive days, every 3 weeks in a 6-week cycle). The primary end point was overall survival (OS). Key secondary end points included progression-free survival (PFS) and objective response rate (ORR). RESULTS Among 461 randomly assigned patients, 229 received liposomal irinotecan and 232 received topotecan. The median follow-up was 18.4 months. The median OS was 7.9 months with liposomal irinotecan versus 8.3 months with topotecan (hazard ratio [HR], 1.11 [95% CI, 0.90 to 1.37]; P = .31). The median PFS per blinded independent central review (BICR) was 4.0 months with liposomal irinotecan and 3.3 months with topotecan (HR, 0.96 [95% CI, 0.77 to 1.20]; nominal P = .71); ORR per BICR was 44.1% (95% CI, 37.6 to 50.8) and 21.6% (16.4 to 27.4), respectively. Overall, 42.0% and 83.4% of patients receiving liposomal irinotecan and topotecan, respectively, experienced grade >= 3 related treatment-emergent adverse events (TEAEs). The most common grade >= 3 related TEAEs were diarrhea (13.7%), neutropenia (8.0%), and decreased neutrophil count (4.4%) with liposomal irinotecan and neutropenia (51.6%), anemia (30.9%), and leukopenia (29.1%) with topotecan. CONCLUSION Liposomal irinotecan and topotecan demonstrated similar median OS and PFS in patients with relapsed SCLC. Although the primary end point of OS was not met, liposomal irinotecan demonstrated a higher ORR than topotecan. The safety profile of liposomal irinotecan was consistent with its known safety profile; no new safety concerns emerged

Large-scale assessment of pros and cons of autopsy-derived or tumor-matched tissues as the norms for gene expression analysis in cancers.

Normal tissues are essential for studying disease-specific differential gene expression. However, healthy human controls are typically available only in postmortal/autopsy settings. In cancer research, fragments of pathologically normal tissue adjacent to tumor site are frequently used as the controls. However, it is largely underexplored how cancers can systematically influence gene expression of the neighboring tissues. Here we performed a comprehensive pan-cancer comparison of molecular profiles of solid tumor-adjacent and autopsy-derived healthy normal tissues. We found a number of systemic molecular differences related to activation of the immune cells, intracellular transport and autophagy, cellular respiration, telomerase activation, p38 signaling, cytoskeleton remodeling, and reorganization of the extracellular matrix. The tumor-adjacent tissues were deficient in apoptotic signaling and negative regulation of cell growth including G2/M cell cycle transition checkpoint. We also detected an extensive rearrangement of the chemical perception network. Molecular targets of 32 and 37 cancer drugs were over- or underexpressed, respectively, in the tumor-adjacent norms. These processes may be driven by molecular events that are correlated between the paired cancer and adjacent normal tissues, that mostly relate to inflammation and regulation of intracellular molecular pathways such as the p38, MAPK, Notch, and IGF1 signaling. However, using a model of macaque postmortal tissues we showed that for the 30 min - 24-hour time frame at 4ºC, an RNA degradation pattern in lung biosamples resulted in an artifact differential expression profile for 1140 genes, although no differences could be detected in liver. Thus, such concerns should be addressed in practice

Large-scale assessment of pros and cons of autopsy-derived or tumor-matched tissues as the norms for gene expression analysis in cancers

Normal tissues are essential for studying disease-specific differential gene expression. However, healthy human controls are typically available only in postmortal/autopsy settings. In cancer research, fragments of pathologically normal tissue adjacent to tumor site are frequently used as the controls. However, it is largely underexplored how cancers can systematically influence gene expression of the neighboring tissues. Here we performed a comprehensive pan-cancer comparison of molecular profiles of solid tumor-adjacent and autopsy-derived “healthy” normal tissues. We found a number of systemic molecular differences related to activation of the immune cells, intracellular transport and autophagy, cellular respiration, telomerase activation, p38 signaling, cytoskeleton remodeling, and reorganization of the extracellular matrix. The tumor-adjacent tissues were deficient in apoptotic signaling and negative regulation of cell growth including G2/M cell cycle transition checkpoint. We also detected an extensive rearrangement of the chemical perception network. Molecular targets of 32 and 37 cancer drugs were over- or underexpressed, respectively, in the tumor-adjacent norms. These processes may be driven by molecular events that are correlated between the paired cancer and adjacent normal tissues, that mostly relate to inflammation and regulation of intracellular molecular pathways such as the p38, MAPK, Notch, and IGF1 signaling. However, using a model of macaque postmortal tissues we showed that for the 30 min – 24-hour time frame at 4ºC, an RNA degradation pattern in lung biosamples resulted in an artifact “differential” expression profile for 1140 genes, although no differences could be detected in liver. Thus, such concerns should be addressed in practice