Carbon dating cancer: defining the chronology of metastatic progression in colorectal cancer

Resveratrol and p53: How are they involved in CRC plasticity and apoptosis?

BACKGROUND

Colorectal cancer (CRC), which is mainly caused by epigenetic and lifestyle factors, is very often associated with functional plasticity during its development. In addition, the malignant plasticity of CRC cells underscores one of their survival abilities to functionally adapt to specific stresses, including inflammation, that occur during carcinogenesis. This leads to the generation of various subsets of cancer cells with phenotypic diversity and promotes epithelial-mesenchymal transition (EMT), formation of cancer cell stem cells (CSCs) and metabolic reprogramming. This can enhance cancer cell differentiation and facilitate tumorigenic potential, drug resistance and metastasis.

AIM OF REVIEW

The tumor protein p53 acts as one of the central suppressors of carcinogenesis by regulating its target genes, whose proteins are involved in the plasticity of cancer cells, autophagy, cell cycle, apoptosis, DNA repair. The aim of this review is to summarize the latest published research on resveratrol's effect in the prevention of CRC, its regulatory actions, specifically on the p53 pathway, and its treatment options.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Resveratrol, a naturally occurring polyphenol, is a potent inducer of a variety of tumor-controlling. However, the underlying mechanisms linking the p53 signaling pathway to the functional anti-plasticity effect of resveratrol in CRC are still poorly understood. Therefore, this review discusses novel relationships between anti-cellular plasticity/heterogeneity, pro-apoptosis and modulation of tumor protein p53 signaling in CRC oncogenesis, as one of the crucial mechanisms by which resveratrol prevents malignant phenotypic changes leading to cell migration and drug resistance, thus improving the ongoing treatment of CRC.

Clinical characteristics and prognostic factors in nasopharyngeal carcinoma with brain metastasis: A retrospective, single-center study

BACKGROUND

Brain metastasis is rare in nasopharyngeal carcinoma (NPC), with only anecdotal cases reported. Conducting a systematic study is crucial for improving the management of these patients.

MATERIALS AND METHODS

Forty-one patients with brain metastasis were retrospectively included between February 2000 and February 2023. The clinical characteristics and treatment information of patients were analyzed. Overall survival (OS) was estimated by Kaplan-Meier survival analysis, and Cox proportional hazard regression analysis was performed to explore prognostic factors.

RESULTS

The median OS for patients was 11.2 months, with a 3-year OS rate of 16.3%. The number of extracranial metastatic organs (HR = 5.533, P = 0.041) and the response of extracranial tumors to treatment (HR = 0.079, P = 0.003) were independent prognostic factors in the cohort.

CONCLUSIONS

Brain metastasis in NPC is a devastating condition that commonly occurs through hematogenous dissemination. Systemic therapy remains fundamental treatment, while local therapy for brain metastases may further improve survival in selected patients.

State-dependent evolutionary models reveal modes of solid tumour growth

Spatial properties of tumour growth have profound implications for cancer progression, therapeutic resistance and metastasis. Yet, how spatial position governs tumour cell division remains difficult to evaluate in clinical tumours. Here, we demonstrate that faster division on the tumour periphery leaves characteristic genetic patterns, which become evident when a phylogenetic tree is reconstructed from spatially sampled cells. Namely, rapidly dividing peripheral lineages branch more extensively and acquire more mutations than slower-dividing centre lineages. We develop a Bayesian state-dependent evolutionary phylodynamic model (SDevo) that quantifies these patterns to infer the differential division rates between peripheral and central cells. We demonstrate that this approach accurately infers spatially varying birth rates of simulated tumours across a range of growth conditions and sampling strategies. We then show that SDevo outperforms state-of-the-art, non-cancer multi-state phylodynamic methods that ignore differential sequence evolution. Finally, we apply SDevo to single-time-point, multi-region sequencing data from clinical hepatocellular carcinomas and find evidence of a three- to six-times-higher division rate on the tumour edge. With the increasing availability of high-resolution, multi-region sequencing, we anticipate that SDevo will be useful in interrogating spatial growth restrictions and could be extended to model non-spatial factors that influence tumour progression.

Colorectal Cancer Stage at Diagnosis Before vs During the COVID-19 Pandemic in Italy

IMPORTANCE

Delays in screening programs and the reluctance of patients to seek medical attention because of the outbreak of SARS-CoV-2 could be associated with the risk of more advanced colorectal cancers at diagnosis.

OBJECTIVE

To evaluate whether the SARS-CoV-2 pandemic was associated with more advanced oncologic stage and change in clinical presentation for patients with colorectal cancer.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective, multicenter cohort study included all 17 938 adult patients who underwent surgery for colorectal cancer from March 1, 2020, to December 31, 2021 (pandemic period), and from January 1, 2018, to February 29, 2020 (prepandemic period), in 81 participating centers in Italy, including tertiary centers and community hospitals. Follow-up was 30 days from surgery.

EXPOSURES

Any type of surgical procedure for colorectal cancer, including explorative surgery, palliative procedures, and atypical or segmental resections.

MAIN OUTCOMES AND MEASURES

The primary outcome was advanced stage of colorectal cancer at diagnosis. Secondary outcomes were distant metastasis, T4 stage, aggressive biology (defined as cancer with at least 1 of the following characteristics: signet ring cells, mucinous tumor, budding, lymphovascular invasion, perineural invasion, and lymphangitis), stenotic lesion, emergency surgery, and palliative surgery. The independent association between the pandemic period and the outcomes was assessed using multivariate random-effects logistic regression, with hospital as the cluster variable.

RESULTS

A total of 17 938 patients (10 007 men [55.8%]; mean [SD] age, 70.6 [12.2] years) underwent surgery for colorectal cancer: 7796 (43.5%) during the pandemic period and 10 142 (56.5%) during the prepandemic period. Logistic regression indicated that the pandemic period was significantly associated with an increased rate of advanced-stage colorectal cancer (odds ratio [OR], 1.07; 95% CI, 1.01-1.13; P = .03), aggressive biology (OR, 1.32; 95% CI, 1.15-1.53; P < .001), and stenotic lesions (OR, 1.15; 95% CI, 1.01-1.31; P = .03).

CONCLUSIONS AND RELEVANCE

This cohort study suggests a significant association between the SARS-CoV-2 pandemic and the risk of a more advanced oncologic stage at diagnosis among patients undergoing surgery for colorectal cancer and might indicate a potential reduction of survival for these patients.

Identification of the effects of COVID-19 on patients with pulmonary fibrosis and lung cancer: a bioinformatics analysis and literature review

Coronavirus disease 2019 (COVID-19) poses a serious threat to human health and life. The effective prevention and treatment of COVID-19 complications have become crucial to saving patients’ lives. During the phase of mass spread of the epidemic, a large number of patients with pulmonary fibrosis and lung cancers were inevitably infected with the SARS-CoV-2 virus. Lung cancers have the highest tumor morbidity and mortality rates worldwide, and pulmonary fibrosis itself is one of the complications of COVID-19. Idiopathic lung fibrosis (IPF) and various lung cancers (primary and metastatic) become risk factors for complications of COVID-19 and significantly increase mortality in patients. Therefore, we applied bioinformatics and systems biology approaches to identify molecular biomarkers and common pathways in COVID-19, IPF, colorectal cancer (CRC) lung metastasis, SCLC and NSCLC. We identified 79 DEGs between COVID-19, IPF, CRC lung metastasis, SCLC and NSCLC. Meanwhile, based on the transcriptome features of DSigDB and common DEGs, we identified 10 drug candidates. In this study, 79 DEGs are the common core genes of the 5 diseases. The 10 drugs were found to have positive effects in treating COVID-19 and lung cancer, potentially reducing the risk of pulmonary fibrosis.

Cancer evolution: Darwin and beyond

Clinical and laboratory studies over recent decades have established branched evolution as a feature of cancer. However, while grounded in somatic selection, several lines of evidence suggest a Darwinian model alone is insufficient to fully explain cancer evolution. First, the role of macroevolutionary events in tumour initiation and progression contradicts Darwin's central thesis of gradualism. Whole-genome doubling, chromosomal chromoplexy and chromothripsis represent examples of single catastrophic events which can drive tumour evolution. Second, neutral evolution can play a role in some tumours, indicating that selection is not always driving evolution. Third, increasing appreciation of the role of the ageing soma has led to recent generalised theories of age-dependent carcinogenesis. Here, we review these concepts and others, which collectively argue for a model of cancer evolution which extends beyond Darwin. We also highlight clinical opportunities which can be grasped through targeting cancer vulnerabilities arising from non-Darwinian patterns of evolution.

Computing nearest neighbour interchange distances between ranked phylogenetic trees

Many popular algorithms for searching the space of leaf-labelled (phylogenetic) trees are based on tree rearrangement operations. Under any such operation, the problem is reduced to searching a graph where vertices are trees and (undirected) edges are given by pairs of trees connected by one rearrangement operation (sometimes called a move). Most popular are the classical nearest neighbour interchange, subtree prune and regraft, and tree bisection and reconnection moves. The problem of computing distances, however, is [Formula: see text]-hard in each of these graphs, making tree inference and comparison algorithms challenging to design in practice. Although anked phylogenetic trees are one of the central objects of interest in applications such as cancer research, immunology, and epidemiology, the computational complexity of the shortest path problem for these trees remained unsolved for decades. In this paper, we settle this problem for the ranked nearest neighbour interchange operation by establishing that the complexity depends on the weight difference between the two types of tree rearrangements (rank moves and edge moves), and varies from quadratic, which is the lowest possible complexity for this problem, to [Formula: see text]-hard, which is the highest. In particular, our result provides the first example of a phylogenetic tree rearrangement operation for which shortest paths, and hence the distance, can be computed efficiently. Specifically, our algorithm scales to trees with tens of thousands of leaves (and likely hundreds of thousands if implemented efficiently).

Clonal Evolution and Timing of Metastatic Colorectal Cancer

Colorectal cancer (CRC) is the third most frequently diagnosed cancer worldwide, where ~50% of patients develop metastasis, despite current improved management. Genomic characterisation of metastatic CRC, and elucidating the effects of therapy on the metastatic process, are essential to help guide precision medicine. Multi-region whole-exome sequencing was performed on 191 sampled tumour regions of patient-matched therapy-naïve and treated CRC primary tumours (n = 92 tumour regions) and metastases (n = 99 tumour regions), in 30 patients. Somatic variants were analysed to define the origin, composition, and timing of seeding in the metastatic progression of therapy-naïve and treated metastatic CRC. High concordance, with few genomic differences, was observed between primary CRC and metastases. Most cases supported a late dissemination model, via either monoclonal or polyclonal seeding. Polyclonal seeding appeared more common in therapy-naïve metastases than in treated metastases. Whereby, treatment prompted for the selection of distinct resistant clones, through monoclonal seeding to distant metastatic sites. Overall, this study reinforces the importance of early clinical detection and surgical excision of the CRC tumour, whilst further highlighting the clinical challenges for metastatic CRC with increased intratumour heterogeneity (either due to early dissemination or polyclonal metastatic spread) and the underlying risk of future therapeutic resistance in treated patients.

Circulating Tumour DNAs and Non-Coding RNAs as Liquid Biopsies for the Management of Colorectal Cancer Patients

Circulating tumour DNAs and non-coding RNAs present in body fluids have been under investigation as tools for cancer diagnosis, disease monitoring, and prognosis for many years. These so-called liquid biopsies offer the opportunity to obtain information about the molecular make-up of a cancer in a minimal invasive way and offer the possibility to implement theranostics for precision oncology. Furthermore, liquid biopsies could overcome the limitations of tissue biopsies in capturing the complexity of tumour heterogeneity within the primary cancer and among different metastatic sites. Liquid biopsies may also be implemented to detect early tumour formation or to monitor cancer relapse of response to therapy with greater sensitivity compared with the currently available protein-based blood biomarkers. Most colorectal cancers are often diagnosed at late stages and have a high mortality rate. Hence, biomolecules as nucleic acids present in liquid biopsies might have prognostic potential and could serve as predictive biomarkers for chemotherapeutic regimens. This review will focus on the role of circulating tumour DNAs and non-coding RNAs as diagnostic, prognostic, and predictive biomarkers in the context of colorectal cancer.

Photoconversion and chromatographic microfluidic system reveals differential cellular phenotypes of adhesion velocity versus persistence in shear flow

An integrated photoconversion and cell sorting parallel-plate chromatography channel enabling the measurement of instantaneous and average velocities of cells mediating adhesion in flow fields was engineered to study the mechanisms underlying adhesion to selectins by metastatic cancer cells. Through the facile enrichment of cells into subfractions of differing adhesive behaviors and a fluorescent velocity probe amenable to off-chip analysis, underlying, causal molecular profiles implicated in differing adhesive phenotypes of metastatic cancer cells could be interrogated. This analytical method revealed selectin-mediated rolling adhesion to be strongly associated with expression of selectin ligands, correlations that vary with ligand type and rolling velocity magnitude. Discrete selectin ligand expression profiles were also found to underlie persistent versus non-persistent adhesion on selectins, suggestive of divergent regulatory mechanisms. This integrated cell sorting and photoconversion microfluidic platform thus enables in vitro analysis and comparisons of adhesive phenotypes as they relate to mechanisms of cancer cell metastasis in the context of selectin mediated adhesion, revealing new insights into potential cancer dissemination pathways.

Metastasis and the evolution of dispersal

Despite significant progress in oncology, metastasis remains the leading cause of mortality of cancer patients. Understanding the foundations of this phenomenon could help contain or even prevent it. As suggested by many ecologists and cancer biologists, metastasis could be considered through the lens of biological dispersal: the movement of cancer cells from their birth site (the primary tumour) to other habitats where they resume proliferation (metastatic sites). However, whether this model can consistently be applied to the emergence and dynamics of metastasis remains unclear. Here, we provide a broad review of various aspects of the evolution of dispersal in ecosystems. We investigate whether similar ecological and evolutionary principles can be applied to metastasis, and how these processes may shape the spatio-temporal dynamics of disseminating cancer cells. We further discuss complementary hypotheses and propose experimental approaches to test the relevance of the evolutionary ecology of dispersal in studying metastasis.

Rapid evolution and biogeographic spread in a colorectal cancer

How and when tumoral clones start spreading to surrounding and distant tissues is currently unclear. Here we leveraged a model-based evolutionary framework to investigate the demographic and biogeographic history of a colorectal cancer. Our analyses strongly support an early monoclonal metastatic colonization, followed by a rapid population expansion at both primary and secondary sites. Moreover, we infer a hematogenous metastatic spread under positive selection, plus the return of some tumoral cells from the liver back to the colon lymph nodes. This study illustrates how sophisticated techniques typical of organismal evolution can provide a detailed, quantitative picture of the complex tumoral dynamics over time and space.

The clonal origins of metastases and the timing of dissemination remains an open question for most cancer types. Using primary and metastatic samples taken from one colorectal cancer patient, Alves et al. use Bayesian phylogenetics to reconstruct the history of metastasis.

Prognostic significance of number versus location of positive mesenteric nodes in stage iii colon cancer

INTRODUCTION

Debate persists on the ideal extent of lymphadenectomy for colon cancer (CC). Specifically, it is unknown whether the anatomical location of positive lymph nodes (LN) has any independent prognostic significance. We assessed the prognostic value of positive LN location in stage III CC patients who underwent extensive (D3) lymphadenectomy.

METHODS

Patients from Kanagawa Cancer Center, Japan, who underwent D3 dissection for CC from 2000 to 16 were analyzed. Mesenteric LN were classified according to location as paracolic (L1), intermediate (L2), or central (L3). Recurrence-free survival (RFS) and the corresponding hazard function were evaluated with their trends over the L groups. Multivariate Cox models were used to evaluate the association of LN location with RFS.

RESULTS

Four hundred forty-six stage III patients were analyzed. The mean number of examined/positive nodes per patient was 42.5/2.6 in L1 (n = 310), 40.9/4.8 in L2 (n = 111), and 44.0/9.8 in L3 (n = 25). RFS was worse for L3 vs. L2 (HR: 2.00, 95%CI [1.05-3.75], p = 0.034) and for L3 vs. L1 (2.62 [1.45-4.71], p = 0.001), but not significantly different between L2 and L1 (1.32 [0.89-1.5], p = 0.17). In a multivariate model adjusting for age, tumor size, and number of lymph nodes harvested T-stage (p < 0.001), adjuvant therapy (p < 0.0038), lymphatic invasion (p = 0.023), and LNR (p = 0.038) were significantly associated with RFS, but not L level or tumor location.

CONCLUSION

The anatomical location of invaded LN does not significantly correlate with RFS in CC, after adjusting for potential confounders. Central LN are infrequently invaded and confer a worse RFS.

Identification and Verification of Two Novel Differentially Expressed Proteins from Non-neoplastic Mucosa and Colorectal Carcinoma Via iTRAQ Combined with Liquid Chromatography-Mass Spectrometry

Recurrence or metastasis of colorectal cancer (CRC) is common following surgery and/or adjuvant therapy, particularly in patients with an advanced stage of the cancer. Identifying key molecular markers of CRC is beneficial for early diagnosis and early treatment, which may eventually improve the prognosis of patients with CRC. Isobaric mass tags for relative and absolute quantification (iTRAQ) in combination with multidimensional liquid chromatography and tandem mass spectrometry (LC-MS/MS) were used to identify differentially expressed proteins between CRC tissues and paired adjacent normal mucosa. Among the 105 patients, adenocarcinoma was the most common CRC subtype, stage III was the most common Tumor-Node-Metastasis stage and high levels of Ki-67 indicated the rapid proliferation of tumor cells in the samples. The LC-MS/MS-based iTRAQ technology identified 271 differentially expressed proteins, with 130 upregulated proteins and 141 downregulated proteins. Bioinformatics analysis revealed that golgin subfamily A member 2 (GOLGA2) and heterogeneous nuclear ribonucleoprotein D0 (hnRNPD) were located in the center of the upregulated protein network, and were closely associated with the development of CRC. The upregulation of GOLGA2 and hnRNPD was further verified in human tissues using western blotting and immunohistochemistry. GOLGA2 and hnRNPD were identified as two novels differentially expressed proteins in human CRC. Furthermore, the LC-MS/MS-based iTRAQ proteomic approach is a useful tool for searching and identifying differentially expressed proteins, and may be used to provide a comprehensive understanding of the processes that mediate the development of CRC.

Analyzing Mechanisms of Metastatic Cancer Cell Adhesive Phenotype Leveraging Preparative Adhesion Chromatography Microfluidic

An integrated, parallel-plate microfluidic device is engineered to interrogate and fractionate cells based on their adhesivity to a substrate surface functionalized with adhesive ligand in a tightly controlled flow environment to elucidate associated cell-intrinsic pathways. Wall shear stress levels and endothelial presentation of E-selectin are modeled after the inflamed vasculature microenvironment in order to simulate in vitro conditions under which in vivo hematogenous metastasis occurs. Based on elution time from the flow channel, the collection of separate fractions of cells-noninteracting and interacting-at high yields and viabilities enables multiple postperfusion analyses, including flow cytometry, in vivo metastasis modeling, and transcriptomic analysis. This platform enables the interrogation of flow-regulated cell molecular profiles, such as (co)expression levels of natively expressed selectin ligands sLex , CD44, and carcinoembryonic antigen, and cancer stem cell marker CD24. This additionally reveals E-selectin adhesivity exhibited by metastatic human colon carcinoma cells to be a transient phenotype. Facile and rapid, this methodology for unbiased, label free sorting of large populations of cells based on their adhesion in flow represents a method of studying flow-regulated adhesion in vitro for the identification of molecular drug targets for development as antimetastatic cancer therapeutics.

Fluorometric Quantification of Single-Cell Velocities to Investigate Cancer Metastasis

Hematogenous metastasis is a multistep, selectin-regulated process whose mechanisms remain poorly understood. To investigate this biological pathway of cancer dissemination and better understand circulating cancer cells, we developed a high-throughput methodology that integrates organ-on-chip-like microfluidic and photoconvertible protein technologies. Our approach can ascribe single-cell velocity as a traceable cell property for off-chip analysis of the direct relationships between cell molecular profiles and adhesive phenotypes in the context of physiologically relevant fluid flow. We interrogate how natively expressed selectin ligands relate to colon cancer cell rolling frequencies and velocities and provide context for previously reported disparities in in vitro and in vivo models of selectin-mediated adhesion and metastasis. This integrated methodology represents a versatile approach for the development of anti-metastatic therapeutics as well as to generate and test mechanistic hypotheses regarding spatiotemporal processes that occur over timescales of seconds to hours with single-cell resolution.

Longitudinal Liquid Biopsy and Mathematical Modeling of Clonal Evolution Forecast Time to Treatment Failure in the PROSPECT-C Phase II Colorectal Cancer Clinical Trial

Sequential profiling of plasma cell-free DNA (cfDNA) holds immense promise for early detection of patient progression. However, how to exploit the predictive power of cfDNA as a liquid biopsy in the clinic remains unclear. RAS pathway aberrations can be tracked in cfDNA to monitor resistance to anti-EGFR monoclonal antibodies in patients with metastatic colorectal cancer. In this prospective phase II clinical trial of single-agent cetuximab in RAS wild-type patients, we combine genomic profiling of serial cfDNA and matched sequential tissue biopsies with imaging and mathematical modeling of cancer evolution. We show that a significant proportion of patients defined as RAS wild-type based on diagnostic tissue analysis harbor aberrations in the RAS pathway in pretreatment cfDNA and, in fact, do not benefit from EGFR inhibition. We demonstrate that primary and acquired resistance to cetuximab are often of polyclonal nature, and these dynamics can be observed in tissue and plasma. Furthermore, evolutionary modeling combined with frequent serial sampling of cfDNA allows prediction of the expected time to treatment failure in individual patients. This study demonstrates how integrating frequently sampled longitudinal liquid biopsies with a mathematical framework of tumor evolution allows individualized quantitative forecasting of progression, providing novel opportunities for adaptive personalized therapies.Significance: Liquid biopsies capture spatial and temporal heterogeneity underpinning resistance to anti-EGFR monoclonal antibodies in colorectal cancer. Dense serial sampling is needed to predict the time to treatment failure and generate a window of opportunity for intervention. Cancer Discov; 8(10); 1270-85. ©2018 AACR. See related commentary by Siravegna and Corcoran, p. 1213 This article is highlighted in the In This Issue feature, p. 1195.

Inferring parsimonious migration histories for metastatic cancers

Metastasis is the migration of cancerous cells from a primary tumor to other anatomical sites. Although metastasis was long thought to result from monoclonal seeding, or single cellular migrations, recent phylogenetic analyses of metastatic cancers have reported complex patterns of cellular migrations between sites, including polyclonal migrations and reseeding. However, accurate determination of migration patterns from somatic mutation data is complicated by intratumor heterogeneity and discordance between clonal lineage and cellular migration. We introduce MACHINA, a multi-objective optimization algorithm that jointly infers clonal lineages and parsimonious migration histories of metastatic cancers from DNA sequencing data. MACHINA analysis of data from multiple cancers shows that migration patterns are often not uniquely determined from sequencing data alone and that complicated migration patterns among primary tumors and metastases may be less prevalent than previously reported. MACHINA's rigorous analysis of migration histories will aid in studies of the drivers of metastasis.

Multicenter phase II study of apatinib treatment for metastatic gastric cancer after failure of second-line chemotherapy

Apatinib is a tyrosine kinase inhibitor and vascular endothelial growth factor receptor 2 (VEGFR-2) targeted drug. A phase I clinical trial showed that this agent has antitumor activity in Chinese patients with metastatic gastric cancer (mGC). The aim of this study was to investigate the safety and efficacy of apatinib treatment in patients with mGC.

This was an open-label, multicenter, single-arm study involving four institutions in China. We enrolled 42 patients from March 2015 to October 2015 who experienced tumor progression after second-line chemotherapy and had no other treatment options that clearly conferred a survival benefit. Oral apatinib (850 mg daily) was administered within 30 min of eating breakfast, lunch, or dinner on days 1 through 28 of each 4-week cycle.

The median progression-free survival (PFS) time and median overall survival (OS) time were 4.0 months (95% CI, 2.85-5.15) and 4.50 months (95% CI, 4.03-4.97), respectively. The disease control rate (DCR) and objective response rate (ORR) were, respectively, 78.57% and 9.52% after 2 cycles and 57.14% and 19.05% after 4 cycles. The main adverse events (AEs) were secondary hypertension, elevated aminotransferase, and hand-foot syndrome, with incidences of 35.71%, 45.24%, and 40.48%, respectively. The most common grade 3 to 4 AEs were secondary hypertension and elevated aminotransferase, with incidences of 7.14% each.

Apatinib is effective and safe in heavily pretreated patients with mGC who fail to respond to two or more prior chemotherapy regimens. Toxicities were tolerable or could be clinically managed.