The detection and analysis of cell-free DNA in patients’ blood are becoming increasingly accepted in oncology. However, this approach has generally been applied for the monitoring of patients with existing tumors. It has not been useful for early diagnosis of cancer because of insufficient sensitivity to detect really small tumors that only shed minute quantities of DNA into the blood, as well as difficulties with identifying cancer-associated genetic changes without knowing what mutations are present in the primary tumor. A method developed by Phallen et al., called targeted error correction sequencing, addresses both of these limitations and demonstrates the feasibility of detecting circulating cell-free DNA from many early tumors, suggesting its potential use for cancer screening. 
 
 Early detection and intervention are likely to be the most effective means for reducing morbidity and mortality of human cancer. However, development of methods for noninvasive detection of early-stage tumors has remained a challenge. We have developed an approach called targeted error correction sequencing (TEC-Seq) that allows ultrasensitive direct evaluation of sequence changes in circulating cell-free DNA using massively parallel sequencing. We have used this approach to examine 58 cancer-related genes encompassing 81 kb. Analysis of plasma from 44 healthy individuals identified genomic changes related to clonal hematopoiesis in 16% of asymptomatic individuals but no alterations in driver genes related to solid cancers. Evaluation of 200 patients with colorectal, breast, lung, or ovarian cancer detected somatic mutations in the plasma of 71, 59, 59, and 68%, respectively, of patients with stage I or II disease. Analyses of mutations in the circulation revealed high concordance with alterations in the tumors of these patients. In patients with resectable colorectal cancers, higher amounts of preoperative circulating tumor DNA were associated with disease recurrence and decreased overall survival. These analyses provide a broadly applicable approach for noninvasive detection of early-stage tumors that may be useful for screening and management of patients with cancer. 
 
 Here, we have developed an ultrasensitive approach for direct analysis of sequence alterations in commonly altered cancer genes in cfDNA without prior knowledge of alterations in the tumor. The sensitivity and specificity of the methodology were evaluated in a clinically relevant cohort of healthy individuals and those with early-stage disease in four common cancers. We identified sequence alterations in cell proliferation genes in individuals without cancer, established the sensitivity of the approach for detecting tumor-specific alterations in the plasma of cancer patients, evaluated concordance between plasma and tumor samples from the same patients, and showed that the amounts of ctDNA can serve as a predictive marker of patient outcome. Overall, these analyses provide information on the potential use and limitations of large-scale mutation-based measurements of ctDNA for early diagnosis in common cancers. 
 
 The development of noninvasive liquid biopsy methods based on the analysis of cell-free DNA (cfDNA) provides the opportunity for a new generation of diagnostic approaches. Although cfDNA in the circulation was first described more than 50 years ago ( 10 ), abnormalities in cancer patients were observed only decades later ( 11 , 12 ) and showed that such individuals have higher amounts of cfDNA. In patients with cancer, a fraction of cfDNA is tumor-derived and is termed circulating tumor DNA (ctDNA). In principle, analysis of ctDNA has the advantage of identifying alterations that are specific to the tumor. The application of next-generation sequencing (NGS), together with advanced computational methods, has recently allowed ctDNA-based tumor genotyping in a variety of cancer types ( 13 – 22 ). However, these approaches have largely been applied in patients with late-stage cancers or have used tumor tissue sequencing to guide mutational analyses in the blood. 
 
 More than 14 million individuals are newly diagnosed with cancer worldwide each year, with the majority having invasive or metastatic disease ( 1 ). It is well established that much of the morbidity and mortality in human cancer is related to the late diagnosis of this disease, where surgical and pharmacologic therapies are less effective ( 2 ). Unfortunately, clinically proven biomarkers that can be used to broadly diagnose and guide patient management early in the course of disease are not available. Serum-based protein biomarkers such as cancer antigen 125, carcinoembryonic antigen (CEA), prostate-specific antigen, and cancer antigen 19-9 are commonly used for monitoring cancer patients, but because these proteins are also found in the serum of individuals without cancer, they are typically not useful for disease diagnosis ( 3 – 7 ). Other approaches for early detection of cancer, such as stool-based molecular tests or colonoscopies, are limited to individual tumor types and have challenges in patient compliance ( 8 , 9 ). Currently, no widely applicable biomarkers have been developed for broad detection of human cancer. 
 
 RESULTS 
 
 Targeted error correction sequencing We developed a methodology for comprehensive analysis of sequence alterations in driver genes that are commonly mutated in colorectal, lung, ovarian, breast, and other cancers. Similar to targeted analyses of cancer tissues (23), we first selected genes that were frequently mutated in these tumors and focused our analyses on either the entire coding regions or the most highly mutated exons of these genes. An analysis of the frequency of these alterations in the COSMIC database of somatic mutations in cancer (24) revealed that more than three quarters of patients would be expected to have at least one mutation in 55 genes among the intended cancers as well as other common tumor types (Table 1 and table S1). We hypothesized that a larger panel of genes would increase the probability of detecting at least one gene alteration in the plasma from any given cancer patient. Because alterations in the blood have previously been reported in healthy individuals, we examined three additional genes as well as specific sequence positions in three genes of the 55-gene panel (table S1) that were known to be somatically altered in clonal hematopoietic expansion, myelodysplasia, or other hematological malignancies (25–27). Table 1. Cancer cases containing alterations in driver genes. View this table: Detection of sequence alterations using conventional NGS is limited to a relatively high fraction of mutant to wild-type DNA (>1%) and, as such, is typically not useful for analyses of ctDNA, which may be present in minute amounts in the blood. Although methods have been developed for analysis of ctDNA in late-stage cancer patients (13–21), no method has been systematically applied for analysis of early-stage disease. We developed a custom capture and sequencing approach called targeted error correction sequencing (TEC-Seq) to allow sensitive and specific detection of low-abundance sequence alterations using NGS (Fig. 1). This methodology is based on targeted capture of multiple regions of the genome and deep sequencing (~30,000×) of DNA fragments. The 58 genes analyzed in this study comprised 80,930 captured bases. Specific steps were performed for analysis of rare tumor-specific alterations in DNA molecules and for elimination of potential amplification, sequencing, and contamination errors as well as other sources of alterations in the blood. These included (i) optimizing library generation and capture for conversion of cfDNA for subsequent analyses; (ii) maximizing representation of unique cfDNA molecules analyzed using mapping positions and a small number of prespecified barcodes; (iii) redundant sequencing, where multiple identical DNA molecules are generated and sequenced and any sequence changes are reconciled; (iv) filtering of mapping and sequencing artifacts; and (v) identifying and removing germline and hematopoietic cell proliferation alterations. Fig. 1. Schematic of the TEC-Seq method. cfDNA is extracted from the blood and converted to a genomic library through ligation of a pool containing a small number of dual-index barcode adapters. The resulting cfDNA library is captured and redundantly sequenced to produce multiple duplicates of each DNA fragment. Sequence reconciliation among duplicate fragments identifies alterations present in identical DNA molecules with the same start and end position and exogenous barcodes. Alignment to the reference genome of multiple distinct molecules containing identical redundant changes is used to identify bona fide alterations. Conceptually, the number of genome equivalents analyzed provides a lower limit of detection for any genomic analysis. A high sensitivity approach would aim to maximize the number of unique molecules assessed while allowing for a broad and facile analysis in a range that is above the actual number of fragments present in a biologic sample. We optimized methodologies for extraction and conversion of cfDNA to genomic libraries. Initially, we considered using the start and end genome mapping positions of paired-end sequenced fragments as “endogenous barcodes” to distinguish between individual molecules. However, Monte Carlo simulations suggested that the tight size distribution of cfDNA molecules observed in the plasma would result in a smaller number of possible end mapping combinations and therefore underestimate the true complexity of cfDNA in the circulation (fig. S1). To extend the complexity of endogenous barcodes, we introduced a limited set of sequence indices as “exogenous barcodes” in the initial steps of library generation. Kinde et al. (28) reported the use of a large number of random exogenous barcodes as unique identifiers for analysis of rare mutations in DNA populations. However, simulations with a relatively small number of long prespecified exogenous barcodes (4-16) suggested that these, in combination with endogenous barcodes, would be sufficient to distinguish among different cfDNA molecules in the plasma from a typical blood draw (fig. S1). Extending the number of barcodes substantially beyond this number has the theoretical disadvantage of misassignment among barcodes through sequencing errors and of primer dimers that can form during library formation. We first evaluated the characteristics of the TEC-Seq approach for detecting known tumor-specific alterations from a mixture of DNA from tumor cell lines at different dilutions (ranging from 100 to 0.1%) with unrelated wild-type DNA. Libraries with eight exogenous barcodes were sequenced with an average of ~32,224 sequence reads at each position among the 58 genes analyzed (table S2). We designed thresholds that were expected to identify >99% of alterations with a mutant allele fraction of 0.5% at the anticipated sequencing depth. Alterations were considered if they were present in all copies of multiple sequences of each DNA molecule with identical endogenous and exogenous barcodes and were not removed by additional error filtering steps. Hotspot alterations at positions previously observed to be frequently altered in cancer patients were evaluated with more sensitive thresholds because the a priori probability that these alterations were tumor-derived is higher than that of other alterations. Alterations present in common germline variant databases or in 25% or greater of reads were considered germline and removed from further analysis, unless the mutations were identical to known hotspot alterations or represented truncating mutations in common tumor suppressor genes. Analysis of the altered positions in the dilution samples revealed high concordance to the expected fraction of mutant molecules (r = 0.93; P < 0.0001, Pearson correlation; fig. S2 and table S2), as well as high sensitivity and specificity. The analytical sensitivity was 97.4% overall and 100 and 89% for detecting mutations present at 0.2 and 0.1%, respectively, using minimum thresholds of 0.05% in hotspot positions and 0.1% at all other locations. No false positives were detected over the 80,930 bases analyzed in 38 dilution analyses, resulting in less than one error in 3 million bases sequenced (error rate of <3.3 × 10−7 false-positive mutation calls per base; specificity, >99.9999%; table S2). 
 
 Evaluation of plasma from healthy individuals We used TEC-Seq to examine plasma specimens from 44 healthy individuals (tables S3 and S4). These individuals were not known to have cancer and provided their blood samples as part of a routine cancer screening visit (colonoscopy or Papanicolaou test). Samples were processed within 2 hours from collection and centrifuged twice at high speed to ensure that cells and cellular debris were removed and that only cfDNA was analyzed. From the ~4 ml of plasma obtained from each individual, we generated TEC-Seq libraries and sequenced these to ~30,000-fold coverage. Through these analyses, no mutations were observed in the cancer driver genes analyzed in our panel, consistent with the estimated specificity observed in our dilution analyses. Although conventional sequencing of these samples would have resulted in thousands of putative alterations among the regions analyzed, the TEC-Seq analyses significantly reduced the sequencing error rate to fewer than one false positive per 3 million bases sequenced (<3 × 10−7 false-positive mutation calls per base; P < 0.0001, paired t test; Fig. 2). We compared the TEC-Seq error rate to those obtained through other liquid biopsy analyses. Reanalysis of our sequence data from 15 healthy individuals using the recently developed integrated digital error suppression (iDES) method (19, 21) resulted in multiple false-positive alterations in the healthy cases, consistent with the reported error rate of this approach (21). Fig. 2. TEC-Seq error correction. Sequencing error rates of conventional NGS and theoretical upper limit for TEC-Seq are indicated at each base in the captured regions of interest (P < 0.0001, paired t test). Error rates are determined by identifying the number of alterations at each base (or assuming one alteration per base if no error was identified) divided by the total coverage at each base among the 44 healthy individuals analyzed. Analysis of six genes related to hematopoietic proliferation identified six individuals with a single mutation in their plasma samples, and a seventh individual had two detectable alterations (16% of patients analyzed; table S5). All of the alterations were identified in DNA methyltransferase 3α (DNMT3A), a gene that is clonally altered under preleukemic conditions and myelodysplasia (25–27). Three of the mutations were predicted to result in the R882C change previously observed in clonal hematopoiesis, but other alterations have not been previously reported. These mutations were identified at mutant allele fractions of 0.16 to 5.3%, substantially lower than previous observations in blood cells of healthy individuals (25–27). Our analyses suggest that a higher fraction of asymptomatic individuals may harbor such somatic alterations than had been previously reported through cellular analyses of these genes in the blood. 
 
 Analysis of plasma from patients with cancer We next analyzed plasma samples from 194 patients with breast cancer (n = 45), colorectal cancer (n = 42), lung cancer (n = 65), and ovarian cancer (n = 42). The cohort consisted of untreated patients who had localized or metastatic disease, with most of the patients diagnosed at stages I and II (table S3). We found that the concentration of cfDNA in plasma from cancer patients was ~29 ng/ml, significantly higher than that observed in healthy individuals (average of 7 ng/ml; P = 0.001, unpaired t test; Fig. 3A). In the colorectal cancer cohort, where a larger number of later-stage patients were analyzed, we found that samples from patients with metastatic disease had higher concentration of cfDNA than those from patients with earlier stages of disease (average of 66 ng/ml for stage IV patients versus 21 ng/ml for stages I to III; P = 0.006, unpaired t test; Fig. 3B). Fig. 3. cfDNA and ctDNA in healthy individuals and patients with cancer. Amount of cfDNA extracted from all healthy individuals and patients with different cancer types (A) and from cancer patients of different stages (B). Mutant allele fraction of ctDNA detected in healthy individuals and patients with different cancer types (C) and in cancer patients of different stages (D). Means for each group are represented by the black bars in the columns analyzed. In patients for whom multiple alterations were detected, the highest value is indicated. Clinical characteristics of patients and stages are indicated in table S3. We examined the cfDNA from these patients using the TEC-Seq approach. Of the 194 patients analyzed, more than three quarters of colorectal cancer patients, two-thirds of ovarian cancer patients, and most of the lung and breast cancer patients had detectable alterations in driver genes (Table 2). These detection rates were higher in some cases than the theoretical estimates for these cancer types (Tables 1 and 2). More than three quarters of patients with advanced disease (stages III and IV) and 62% of patients with localized disease (stages I and II) were detected among all tumor types (Table 2). The amounts of ctDNA varied among cancer types, with breast cancer having the lowest mutant allele fraction (P = 0.028, unpaired t test; Fig. 3C). Similar to observations of cfDNA, the amounts of ctDNA were higher in metastatic disease compared to earlier-stage disease among all cancer types (P < 0.0001, unpaired t test; Figs. 3D and 4). Eighty of 128 detected cases had at least one alteration in a gene hotspot position (Fig. 4). The affected genes and distribution of alterations for each tumor type were similar to common driver gene alterations that have previously been reported in these cancers (fig. S3). On average, 2.1 alterations, including 0.9 changes at hotspot positions, were observed in each patient with detectable ctDNA, with lung and colorectal cancers having a higher number of alterations per case (Fig. 4). By limiting analysis only to a specific set of hotspot variants as others have reported (21), the fraction of cases detected was reduced to 56% of those identified by TEC-Seq. These observations highlight the benefit of analyzing a broader panel of driver gene regions to increase the possibility of detecting tumor-specific alterations in the plasma. Table 2. Cancer patients detected using TEC-Seq. NA, not applicable. View this table: Fig. 4. ctDNA in patients with breast, colorectal, lung, and ovarian cancer. Patients (n = 194) are each represented by a tick mark. (Left) Bar chart shows the number of alterations detected for each case. (Middle) Stage, cancer type, and histopathological subtype are represented by colored vertical bars. (Right) Mutant allele fractions for each alteration detected per patient are indicated with an “x” at the mean. Alterations are colored on the basis of hotspot status and whether any alterations were detected in the case. 
 
 Comparison of mutations in plasma with those in matched tumor and blood cells Of the 194 patients in our study, 152 cases had matched tumor and normal tissues that we analyzed using an independent targeted NGS approach (tables S3 and S4). We examined these cases to determine whether the mutations identified in the plasma were tumor-specific or may have originated during blood cell expansion. The plasma analyses performed using TEC-Seq were performed separately and did not rely on any knowledge of alterations identified through these parallel tissue analyses. We detected 87 changes in the circulation of 194 patients at allele fractions >25% and considered these to be likely germline variants. Analysis of 63 of these variants in the available corresponding blood cells identified all these changes to be germline (table S6). These observations suggested that cfDNA can be used to accurately identify germline changes in the context of tumor-derived and blood cell proliferation alterations and, similarly, that this approach can be used to distinguish these changes from somatic alterations. Similar to our observations in healthy individuals, we identified alterations in DNMT3A and five other genes involved in blood cell proliferation in the plasma of cancer patients (table S5). The fraction of patients with detectable changes in these genes correlated with age, as previously observed (P = 0.013, unpaired t test) (25–27). Unlike tumor-specific alterations, the allele fractions of blood cell proliferation alterations in cfDNA were similar among healthy individuals and patients with cancer, regardless of stage. Analysis of matched white blood cells from individuals with alterations in these genes identified the corresponding mutation in most of the cases, consistent with the notion that the alterations in cfDNA originated from these cells (table S5). After accounting for blood cell proliferation and germline alterations, we identified 313 candidate tumor-specific changes in the plasma samples from 128 of the 194 patients analyzed. We further evaluated 216 of these alterations in 100 patients where matched tumor tissue and blood cells were available. We found that 155 of the 216 (72%) alterations were identical in both plasma and tumor samples (Fig. 5). Among stage III and IV patients, 65 of 84 (77%) variants were concordant, whereas for early-stage patients, 90 of 132 (68%) alterations were concordant. In line with these observations, we found that 70 of the 75 (93%) alterations with a mutant allele fraction >1% in the plasma were detected in the tumor tissue of the same individual. Overall, 82 of the 100 (82%) patients had at least one alteration observed in the circulation that was identical to that in the tumor specimen. Fig. 5. Concordance between alterations in plasma and tissue. Mutant allele fractions observed in the plasma are indicated for each alteration identified with a black bar at the mean. The presence of alterations in matched tumor specimens is indicated with green dots, whereas nonconcordant alterations are indicated in orange, and those that are not assessed are indicated in gray. Stage and cancer type for each patient are plotted in the two horizontal tracks at the bottom of the figure. To evaluate reproducibility of the approach between separate blood draws in the same patients, we assessed six late-stage patients with lung cancer where blood was obtained early during the course of treatment. These patients were undergoing treatment but were observed to have progressive or stable disease. Despite the difference in time between the blood draws, we found that 90% of the alterations observed in the second blood draw were present at the time of the first blood draw (17 of 19 alterations), with one patient having no alterations at both time points (fig. S4). All alterations present with a mutant allele fraction ≥1% were observed at both time points. In a subset of colorectal cancer patients, we evaluated whether the observations we detected in the plasma could be independently confirmed using droplet digital polymerase chain reaction (ddPCR), a method that is highly sensitive for detection of single-base substitutions (29). We examined six driver alterations detected in the plasma: two that were also detected in matched tumors and four that were absent. Five of the six driver alterations were detected in the plasma by ddPCR at levels similar to those observed by TEC-Seq (fig. S5A). Those not detected in tumors by targeted sequencing were similarly not identified through ddPCR approaches. We also evaluated 10 mutations that corresponded to the most common changes in KRAS, PIK3CA, and BRAF that we detected in these tumors but were not present in the plasma of these patients. Although we confirmed that these alterations were in the tumors of these patients, we found that those not detected by TEC-Seq analyses remained undetected by ddPCR in the plasma, presumably because the amounts of ctDNA corresponding to these alterations were extremely low in these patients (fig. S5B). To assess the possibility that tumor heterogeneity may be responsible for the apparent lack of concordance between specific alterations in the plasma and those in the tumor, we analyzed multiple tumor sites from colorectal cancer patient CGCRC307 using ddPCR. We characterized 10 different regions of the tumor as well as a subsequent metastatic site for an R201C alteration in the GNAS gene that we detected in the plasma but not in the tumor of this patient. Although we found a BRAF V600E alteration in all samples analyzed, the GNAS R201C substitution was not detected in the original tumor biopsy but was detected as a subclonal change in only a portion of the primary tumor, suggesting that it developed later in tumorigenesis (fig. S6). The GNAS R201C change identified had been previously reported in colorectal cancers (30) and has been shown to promote intestinal tumorigenesis through activation of both Wnt and ERK pathways (31). Consistent with this notion, we found the GNAS alteration to be clonal in the metastatic lesion that was identified 2 years after the primary tumor in this patient (fig. S6). These results suggest that plasma alterations not detected in the matched tumor specimens may represent bona fide somatic mutations in ctDNA derived from heterogeneous primary or occult lesions. ||||| By Dennis Thompson 
 
 HealthDay Reporter 
 
 (HealthDay) 
 
 WEDNESDAY, Aug. 16, 2017 (HealthDay News) -- A new genetic blood test might pave the way for detecting early stage cancers that often prove fatal when caught too late, a new study suggests. 
 
 The test scans blood for DNA fragments released by cancerous tumors, explained lead researcher Dr. Victor Velculescu. 
 
 By reviewing these DNA fragments for mutations found in 58 "cancer-driver" genes, the blood test detects many early stage cancers without rendering false positives for healthy people, said Velculescu, co-director of cancer biology at the Johns Hopkins Kimmel Cancer Center, in Baltimore. 
 
 The test detected stage 1 or 2 colon, breast, lung or ovarian cancers between 59 percent and 71 percent of the time when assessing 200 patients previously diagnosed with cancer, researchers found. 
 
 "If we are able to detect cancer earlier, our chances of saving lives would be much higher," Velculescu said. "The survival difference between late-stage and early stage disease in these cancers accounts for over a million lives worldwide each year." 
 
 The test also proved capable of screening out cancer-free people. 
 
 Dr. Len Lichtenfeld, deputy chief medical officer for the American Cancer Society, called this "important research" that "moves us one step further down the path to developing a blood test that might find cancer earlier." 
 
 "We still need to improve the sensitivity, but this is a step forward. It is a proof of concept," Lichtenfeld said. "It is not a test that's going to be available in a clinical laboratory anytime soon." 
 
 To develop a genetic blood test for cancer, researchers must find ways to spot DNA mutations linked to cancer while ignoring natural and harmless mutations that regularly occur in humans, Velculescu explained. 
 
 Velculescu and his team developed a genetic scan that essentially "takes a fragment here and a fragment there and uses it to create a picture of what the tumor DNA looks like," Lichtenfeld said. "That's what makes it so elegant." 
 
 The research team assembled a panel of 58 cancer-linked genes, and used their scan to look for tumor DNA fragments in the blood of 200 people known to have cancer. 
 
 Overall, researchers detected about 62 percent of stage 1 and 2 cancers. 
 
 The test specifically spotted early stage colon cancer 71 percent of the time, breast and lung cancer 59 percent of the time, and ovarian cancer 68 percent of the time. 
 
 The ability to catch early stage ovarian cancer is particularly needed, Lichtenfeld said. Fewer than one in five ovarian cancers are caught early, when the five-year survival rate is greater than 90 percent. Most are detected after they've spread, and by then the odds of five-year survival are 40 percent or less, he said. 
 
 "Finding any marker in a stage 1 ovarian cancer patient is very important, because this is a tumor that usually presents at a much later stage," Lichtenfeld said. 
 
 The researchers also directly tested cancerous tissue removed from half of the 200 cancer patients. They found that 82 percent of the tumors contained mutations that correlated with DNA fragments found in the person's blood. 
 
 To check the blood test's ability to weed out healthy people, the researchers also analyzed blood from 44 volunteers without cancer. No false positives occurred. 
 
 That equates to less than one false positive for more than 3.5 million letters of DNA sequenced, since each separate test requires assessment of 80,000 DNA base pairs associated with the 58-gene screening panel, Velculescu said. 
 
 Despite these promising results, researchers need to validate the blood test in larger studies, Velculescu said. 
 
 More work also needs to be done to improve the detection rate, Lichtenfeld added. "These tests were not able to detect 100 percent of the cancers," he said. 
 
 Finally, cancer doctors must discuss what will be done when technology evolves to the point that such tests regularly find tumors that aren't life-threatening, Lichtenfeld said. In some cases, treatment to remove the cancer could be worse than leaving it alone. 
 
 "What's going to be so important is to be able to distinguish cancers that will hurt people versus cancers that may not have long-term impact on survival," Lichtenfeld said. 
 
 The report appears in the Aug. 16 issue of the journal Science Translational Medicine. 
 
 More information 
 
 For more on the genetics of cancer, visit the U.S. National Cancer Institute. ||||| CHICAGO (Reuters) - A test that scans blood for tumor-specific DNA identified early-stage cancer in more than half of 138 patients with the disease, U.S. researchers reported on Wednesday, marking a new milestone in the rush for so-called “liquid biopsies.” 
 
 Several companies already offer tests that can detect cancer DNA in the blood of patients with late-stage cancers. Such tests are used to help guide treatment or identify whether cancers have returned after surgery. 
 
 Researchers behind the early-stage test hope it could be used to identify cancers at a stage when patients have a better chance at survival. 
 
 “To our knowledge, this is one of the first studies that has looked directly at early-stage cancers,” said Dr Victor Velculescu, professor of oncology at Johns Hopkins Kimmel Cancer Center, whose study was published in the journal Science Translational Medicine. 
 
 In making the test, the challenge was to identify rare DNA from real cancers while ignoring other types of genetic alterations that can occur as blood cells divide or genetic alterations that people are born with. 
 
 For the study, the team screened blood samples from patients with breast, lung, ovarian and colorectal cancers, looking for 58 genes typically linked with these cancers. Overall, they were able to detect 86 out of 138 stage I and stage II cancers. They also sequenced mutations in tumors from 100 of the patients studied, and found that in 82 patients, the same mutations found in the blood corresponded with those found in the tumor tissue. 
 
 They also tried the test on 44 healthy patients, and showed it did not detect any cancer-derived mutations. 
 
 Velculescu said more studies would be needed in much larger populations to prove the test can safely and accurately identify early-stage cancers, a process that could take up to five years. 
 
 The hope, he said, is that it would identify cancers at a stage when patients have a better chance at survival. First uses of the technology would be in patients at high risk for developing cancer, such as heavy smokers, he said. 
 
 In addition to being a researcher at Johns Hopkins, Velculescu is a co-founder of Personal Genome Diagnostics, a private liquid biopsy company. The study was done by Johns Hopkins researchers, he said. 
 
 In June, Grail, a spinoff from gene sequencer maker Illumina, presented a feasibility study for its liquid biopsy test at American Society of Clinical Oncology meeting in Chicago. In that study, researchers analyzed tissue and blood from patients with advanced cancers. Grail is also pursuing early-stage cancer detection.
– Human blood is rich with genetic material, and scientists have in recent years taken many steps forward in decoding it. The latest announcement—that a blood test can spot cancer at its earliest stages—has the potential to save millions of lives as treatment is administered earlier in the disease's progression, reports Reuters. Reporting in the journal Science Translational Medicine, scientists say that by analyzing DNA fragments in blood to look for several dozen cancer-driver genes, they spotted 86 out of 138 stage 1 and stage 2 cancers; they also confirmed no trace of cancer in 44 healthy patients (in other words, there were zero false positives). Some call this minimally invasive test a "liquid biopsy." "This is one of the first studies that has looked directly at early-stage cancers," says lead author Dr. Victor Velculescu, an oncologist at Johns Hopkins Kimmel Cancer Center. While the test is proof-of-concept and not yet ready for prime time, detecting 62% of cancers that were only in stages 1 or 2 is a major milestone, experts say. For instance, less than one in five ovarian cancers are caught that early, when the survival rate is higher than 90%; those that are caught after the cancer has spread face a dramatically lower 40% survival rate five years out, per HealthDay News. For this study, however, the blood test caught early-stage ovarian cancer 68% of the time. Scientists hope they can get the test much closer to a 100% detection rate. (This cancer treatment is being hailed as the most exciting in a lifetime.)